Intelligent calling method and system for stair-climbing base frame of sweeper

Abstract

The embodiment of the invention provides an intelligent calling method and system for a floor-climbing base frame of a sweeper, and belongs to the technical field of intelligent mobile cleaning equipment. The method comprises the following steps: acquiring call triggering information used for triggering butt joint of the sweeper and a stair climbing base frame, and generating position data containing sweeper positioning data and target operation area data based on the call triggering information; based on the position data, constructing a collaborative navigation path for convergence of the sweeper and the stair-climbing base frame, and using the collaborative navigation path to drive the sweeper and the stair-climbing base frame to execute autonomous movement; executing an approaching action of the sweeper and the stair-climbing base frame based on the collaborative navigation path, and acquiring docking state data reported by the sweeper and the stair-climbing base frame in the approaching process to form docking action data; and the docking action of the sweeper on the stair climbing base frame is completed based on the docking action data, and the floor switching operation of the sweeper is executed according to the target operation area data. According to the scheme, stable, continuous and correctable cooperative scheduling of the sweeper and the stair climbing base frame in a multi-floor environment is realized.

Description

(19) State Intellectual Property Office (12) Invention Patent Application (10) Application Publication Number (43) Application Publication Date (21) Application Number 202511882152.3 (22) Application Date 2025.12.12 (71) Applicant: Zhuimi Innovation Technology (Suzhou) Co., Ltd. Address: Units 1, 2, and 3, Building 8, No. 1688, Songwei Road, Guoxiang Street, Wuzhong Economic Development Zone, Suzhou City, Jiangsu Province, 215000 Applicant: Zhuimi Technology (Suzhou) Co., Ltd. (72) Inventor: Qiu Weinan (74) Patent Agency: Beijing Runping Intellectual Property Agency Co., Ltd. 11283 Patent Attorney: Zheng Haitao (51) Int.Cl. A47L 11 / 40 (2006.01) A47L 11 / 24 (2006.01) (54) Invention Title: Intelligent Summoning Method and System for Sweeping Machine Climbing Staircase (57) Abstract: This invention provides an intelligent summoning method and system for sweeping machine climbing staircase, belonging to the field of intelligent mobile cleaning equipment technology. The method includes: acquiring summoning trigger information for triggering the docking of the sweeping machine and the climbing staircase; generating location data containing sweeping machine positioning data and target work area data based on the summoning trigger information; constructing a collaborative navigation path for the sweeping machine and the climbing staircase to meet based on the location data, and using the collaborative navigation path to drive the sweeping machine and the climbing staircase to perform autonomous movement; performing an approach action between the sweeping machine and the climbing staircase based on the collaborative navigation path, and acquiring docking status data reported by both parties during the approach process to form docking action data; completing the docking action of the sweeping machine to the climbing staircase based on the docking action data, and performing floor switching operation of the sweeping machine according to the target work area data. This invention achieves stable, continuous and correctable collaborative scheduling of the sweeping machine and the climbing staircase in a multi-floor environment. Claims 4 pages, Description 15 pages, Drawings 5 ​​pages, CN 121549721 A 2026.02.24 CN 1 21 54 97 21 A 1. A smart summoning method for a sweeping robot climbing a stair-climbing frame, characterized in that the method includes: acquiring summoning trigger information for triggering the docking of the sweeping robot with the stair-climbing frame; generating location data including sweeping robot positioning data and target work area data based on the summoning trigger information; determining the movable area boundary of the sweeping robot based on the positioning data in the location data, and generating a target meeting point based on the location data of the target work area data; constructing a cooperative navigation path for the docking of the sweeping robot and the stair-climbing frame based on the area boundary and the target meeting point, and using the cooperative navigation path to drive the sweeping robot and the stair-climbing frame to perform autonomous movement; performing an approach action between the sweeping robot and the stair-climbing frame based on the cooperative navigation path, and acquiring docking status data reported by both parties during the approach process to form docking action data;Based on the docking action data, the sweeper completes the docking action with the stair-climbing frame, and performs the floor switching operation of the sweeper according to the target work area data. 2. The method according to claim 1, characterized in that the call trigger information used to trigger the docking of the sweeper with the stair-climbing frame is at least one of automatic trigger data reported by the sweeper and manual trigger data generated by user instructions, wherein the automatic trigger data is generated based on the operating status information automatically reported by the sweeper when it completes the current cleaning task or receives onboard button instructions; the manual trigger data is generated based on the cross-floor movement instructions input by the user through a voice interaction terminal or mobile terminal to generate instruction information to be parsed. 3. The method according to claim 1, characterized in that, obtaining the sweeping robot's call trigger information and generating location data containing sweeping robot positioning data and target work area data based on the call trigger information includes: identifying the location reporting field in the call trigger information and extracting initial positioning information representing the sweeping robot's current spatial coordinates based on the location reporting field; parsing the task status field in the call trigger information and extracting initial call information representing the need for cross-floor movement based on the task status field; wherein, the task status field is a task status identifier field additionally recorded in the call trigger information to represent the sweeping robot's current task stage and cross-floor movement intention; constructing a joint data structure describing the sweeping robot's location attributes and call attributes based on the initial positioning information and the initial call information, and using the joint data structure as the location data. 4. The method according to claim 1, characterized in that, determining the movable area boundary of the sweeping machine based on the positioning data in the location data, generating a target meeting point based on the location data of the target work area data, and constructing a cooperative navigation path for the sweeping machine and the stair-climbing frame to meet based on the area boundary and the target meeting point, includes: parsing the positioning data in the location data to obtain the current spatial orientation information of the sweeping machine, and determining area constraint data for representing the movable area boundary of the sweeping machine based on the spatial orientation information; parsing the location data of the target work area data to obtain target point information for representing the meeting target position, and generating a target meeting point for describing the meeting position of the sweeping machine and the stair-climbing frame based on the target point information; and constructing path description data for describing the respective movement trajectories of the sweeping machine and the stair-climbing frame based on the area constraint data and the target meeting point, thereby forming the cooperative navigation path. 5. The method according to claim 4, characterized in that, based on the regional constraint data and the target meeting point, path description data for describing the respective movement trajectories of the sweeping robot and the stair-climbing frame is constructed to form the cooperative navigation path, comprising: (Claim 1 / 4 page 2 CN 121549721 A)Based on the regional constraint data, a boundary set of the sweeper's walkable area is determined, and movement constraint parameters representing the sweeper's movement restrictions are extracted from the boundary set; wherein, the movement constraint parameters are calculated based on the marked impassable areas and obstacle boundaries in the regional constraint data; based on the target meeting point, the movement direction data of the stair-climbing frame from its current position to the target meeting point is determined, and accessibility parameters representing the stair-climbing frame's mobility are constructed; wherein, the accessibility parameters are calculated based on the spatial connectivity relationship between the stair-climbing frame's current position and the target meeting point; based on the movement constraint parameters and the accessibility parameters, path planning calculations are performed to generate sweeper trajectory data representing the sweeper's movement trajectory and stair-climbing frame trajectory data representing the stair-climbing frame's movement trajectory, respectively; the sweeper trajectory data and the stair-climbing frame trajectory data are combined into path description data. 6. The method according to claim 4, characterized in that, using the cooperative navigation path to drive the sweeper and the stair-climbing frame to perform autonomous movement, includes: extracting sweeper movement command data based on the sweeper trajectory data in the cooperative navigation path, and generating sweeper movement control data representing the sweeper's direction of travel and step length based on the movement command data; extracting stair-climbing frame movement command data based on the stair-climbing frame trajectory data in the cooperative navigation path, and generating stair-climbing frame movement control data representing the stair-climbing frame's direction of travel and step length based on the movement command data; and inputting the sweeper movement control data and the stair-climbing frame movement control data into the autonomous movement execution process, so as to drive the sweeper and the stair-climbing frame to complete autonomous movement along their respective trajectory data and approach the target meeting point. 7. The method according to claim 1, characterized in that, the approach action between the sweeping robot and the stair-climbing frame is performed based on the cooperative navigation path, and docking status data reported by both parties is acquired during the approach process to form docking action data, including: determining the target approach direction of the sweeping robot in the approach phase based on the sweeping robot trajectory data in the cooperative navigation path, and reporting sweeping robot approach status information to indicate changes in sweeping robot posture during the sweeping robot's movement along the target approach direction; determining the target approach direction of the stair-climbing frame in the approach phase based on the stair-climbing frame trajectory data in the cooperative navigation path, and reporting stair-climbing frame approach status information to indicate changes in stair-climbing frame posture during the stair-climbing frame's movement along the target approach direction; when the sweeping robot approach status information and the stair-climbing frame approach status information are both valid, generating alignment relationship data to indicate the real-time alignment relationship between the two parties based on their relative positional relationship; and constructing docking action data to describe the sweeping robot entering the carrying area of ​​the stair-climbing frame based on the alignment relationship data.8. The method according to claim 7, characterized in that, when the sweeper's approach status information and the stair-climbing frame's approach status information are both valid, alignment relationship data representing the real-time alignment relationship between the two is generated based on their relative positional relationship, including: after acquiring the sweeper's approach status information, determining whether the sweeper's approach status information is valid based on preset validity conditions, and extracting sweeper approach posture parameters representing the sweeper's approach posture if valid; after acquiring the stair-climbing frame's approach status information, determining whether the stair-climbing frame's approach status information is valid based on preset validity conditions, and extracting stair-climbing frame approach posture parameters representing the stair-climbing frame's approach posture if valid; wherein, the preset validity conditions are set based on the numerical range and change law corresponding to the sweeper's approach status information and the stair-climbing frame's approach status information, respectively, and are used to determine whether the sweeper's approach status information and the stair-climbing frame's approach status information are in a valid state; Under the condition that both the approach posture parameters of the sweeper and the approach posture parameters of the stair-climbing frame are valid, the relative position offset and relative angle offset of the two are calculated, and alignment relationship data representing the real-time alignment relationship of the two is constructed based on the offset. 9. The method according to claim 1, characterized in that, the sweeper performs the docking action to the stair-climbing frame based on the docking action data, and performs the floor switching operation of the sweeper according to the target work area data, including: generating docking control data to constrain the sweeper to enter the carrying area of ​​the stair-climbing frame based on the docking action data, and generating docking completion confirmation information after the sweeper completes the entry action according to the docking control data; extracting target floor parameters based on the target work area data, and generating floor switching control data according to the target floor parameters; using the floor switching control data to drive the stair-climbing frame to perform the corresponding floor switching process, and releasing the sweeper after reaching the target floor. 10. The method according to claim 9, characterized in that generating docking control data for constraining the sweeper's entry into the load-bearing area of ​​the stair-climbing frame based on the docking action data, and generating docking completion confirmation information after the sweeper completes the entry action according to the docking control data, includes: extracting docking posture parameters representing the sweeper's entry direction and alignment angle based on the docking action data, and generating docking trajectory control data for constraining the sweeper's movement trajectory according to the docking posture parameters; collecting load-bearing position detection information representing the sweeper's arrival at the load-bearing area during the sweeper's entry action according to the docking trajectory control data, and generating docking completion confirmation information when the load-bearing position detection information meets a preset arrival condition. 11. An intelligent summoning system for a sweeper climbing stair-climbing frame, characterized in that the system includes:A triggering unit is used to acquire call trigger information for triggering the docking of the robot vacuum and the stair-climbing frame, and generate location data containing robot vacuum positioning data and target work area data based on the call trigger information; a path planning unit is used to determine the movable area boundary of the robot vacuum based on the positioning data in the location data, and generate a target meeting point based on the location data of the target work area, construct a cooperative navigation path for the robot vacuum and the stair-climbing frame to meet based on the area boundary and the target meeting point, and use the cooperative navigation path to drive the robot vacuum and the stair-climbing frame to perform autonomous movement respectively; a movement unit is used to perform the approach action of the robot vacuum and the stair-climbing frame based on the cooperative navigation path, and acquire docking status data reported by both parties during the approach to form docking action data; a docking unit is used to complete the docking action of the robot vacuum to the stair-climbing frame based on the docking action data, and perform the floor switching operation of the robot vacuum according to the target work area data. 12. A computer-readable storage medium, characterized in that the computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to execute the intelligent summoning method for a sweeper climbing a stair frame as described in any one of claims 1-10. 13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements the intelligent summoning method for a sweeper climbing a stair frame as described in any one of claims 1-10. 14. A computer program product comprising a computer program, characterized in that, when executed by a processor, the computer program implements the intelligent summoning method for a sweeper climbing a stair frame as described in any one of claims 1-10. Claims 4 / 4 Page 5 CN 121549721 A Intelligent Summoning Method and System for a Stair-Climbing Base of a Sweeping Robot Technical Field

[0001] This invention relates to the field of intelligent mobile cleaning equipment technology, specifically to an intelligent summoning method and system for a stair-climbing base of a sweeping robot. Background Art

[0002] In home cleaning scenarios, sweeping robots have become quite mature, and common capabilities such as positioning, mapping, and path planning have gradually become widespread. However, their activity range is mostly limited to a single floor. Once there are stairs in the residence, the sweeping robot basically cannot move across floors on its own, and users can only rely on manual carrying or some relatively fixed auxiliary structures to solve the problem of cross-floor scheduling.

[0003] Some so-called "stair-climbing base" solutions have appeared on the market, but most of them are based on relatively fixed positions.The main issue is that some systems require the base frame to remain stationary at the stairwell entrance, automatically returning to that position after the robot vacuum finishes cleaning; others require the base frame to attempt to locate the robot vacuum after receiving a trigger command. Both are essentially unidirectional search processes. In slightly more complex environments, such as furniture obstructing the view or unstable signals, the robot vacuum and the base frame may "not find" each other. If users encounter this situation, they often need to intervene frequently, and the entire cross-floor scheduling process is not truly automated.

[0004] Another common problem is the relatively simple triggering method. Many products rely on fixed programs or physical buttons to initiate cross-floor actions, and users cannot initiate a cleaning request with floor semantics through more natural methods, such as voice or mobile applications. For multi-story residential buildings, this triggering method is not flexible enough and becomes cumbersome after prolonged use.

[0005] In the approach and docking phase, existing solutions also have limitations. Most base frames rely only on relatively simple infrared proximity or physical guidance structures to complete the final "alignment". These methods are highly dependent on the surrounding environment; slight changes in light, floor material, or furniture arrangement may affect the accuracy of docking or even directly lead to failure. In ordinary household environments, this situation is not uncommon, and it also makes the user experience unstable.

[0006] Overall, the current cross-floor scheduling scheme still has obvious shortcomings in terms of automatic location finding ability, flexibility of triggering methods, and stability of close-range docking, making it difficult to achieve true multi-floor intelligent cleaning. Summary of the Invention

[0007] The purpose of the embodiments of the present invention is to provide an intelligent summoning method and system for a robot vacuum cleaner climbing a stair-climbing frame, so as to at least solve the problems of unstable docking and single triggering methods in the cross-floor scheduling process of the existing scheme.

[0008] To achieve the above objective, the first aspect of the present invention provides an intelligent summoning method for a sweeping robot climbing a stair-climbing frame. The method includes: acquiring summoning trigger information for triggering the docking of the sweeping robot with the stair-climbing frame; generating location data including sweeping robot positioning data and target work area data based on the summoning trigger information; determining the movable area boundary of the sweeping robot based on the positioning data in the location data, and generating a target meeting point based on the location data of the target work area; constructing a collaborative navigation path for the docking of the sweeping robot and the stair-climbing frame based on the area boundary and the target meeting point, and using the collaborative navigation path to drive the sweeping robot and the stair-climbing frame to perform autonomous movement; performing an approach action between the sweeping robot and the stair-climbing frame based on the collaborative navigation path, and acquiring docking status data reported by both parties during the approach process to form docking action data; completing the docking action of the sweeping robot with the stair-climbing frame based on the docking action data, and performing a floor switching operation of the sweeping robot according to the target work area data.

[0009] Optionally, the call trigger information used to trigger the docking of the sweeper with the stair-climbing frame can be at least one of automatically triggered data reported by the sweeper and manually triggered data generated by user commands. The automatically triggered data is generated based on the operating status information automatically reported by the sweeper when it completes the current cleaning task or receives an onboard button command. The manual trigger data is generated based on the cross-floor movement command input by the user through a voice interaction terminal or mobile terminal to generate command information to be parsed.

[0010] Optionally, obtaining the sweeper's call trigger information and generating location data containing sweeper positioning data and target work area data based on the call trigger information includes: identifying the location reporting field in the call trigger information and extracting initial positioning information representing the sweeper's current spatial coordinates based on the location reporting field; parsing the task status field in the call trigger information and extracting initial call information representing the need for cross-floor movement based on the task status field; wherein, the task status field is a task status identifier field additionally recorded in the call trigger information to represent the sweeper's current task stage and cross-floor movement intention; constructing a joint data structure describing the sweeper's location attributes and call attributes based on the initial positioning information and the initial call information, and using this joint data structure as the location data.

[0011] Optionally, the movable area boundary of the sweeping machine is determined based on the positioning data in the location data, and a target meeting point is generated based on the location data of the target work area data. A cooperative navigation path for the sweeping machine and the stair-climbing frame to meet is constructed based on the area boundary and the target meeting point, including: parsing the positioning data in the location data to obtain the current spatial orientation information of the sweeping machine, and determining area constraint data for representing the movable area boundary of the sweeping machine based on the spatial orientation information; parsing the location data of the target work area data to obtain target point information for representing the meeting target position, and generating a target meeting point for describing the meeting position of the sweeping machine and the stair-climbing frame based on the target point information; and constructing path description data for describing the respective movement trajectories of the sweeping machine and the stair-climbing frame based on the area constraint data and the target meeting point, thus forming the cooperative navigation path.

[0012] Optionally, based on the regional constraint data and the target meeting point, path description data is constructed to describe the respective movement trajectories of the sweeping robot and the stair-climbing frame, forming the cooperative navigation path. This includes: determining the boundary set of the sweeping robot's walkable area based on the regional constraint data, and extracting movement constraint parameters representing the sweeping robot's movement restrictions within the boundary set; wherein the movement constraint parameters are calculated based on the marked impassable areas and obstacle boundaries in the regional constraint data; and determining the distance from the stair-climbing frame's current position to the target meeting point based on the target meeting point.The movement direction data of the points are collected, and accessibility parameters are constructed to represent the mobility of the stair-climbing frame. The accessibility parameters are calculated based on the spatial connectivity between the current position of the stair-climbing frame and the target meeting point. Path planning calculations are performed based on the movement constraint parameters and the accessibility parameters to generate sweeper trajectory data and stair-climbing frame trajectory data to represent the movement trajectory of the sweeper and the stair-climbing frame, respectively. The sweeper trajectory data and the stair-climbing frame trajectory data are combined into path description data.

[0013] Optionally, the cooperative navigation path is used to drive the sweeper and the stair-climbing frame to perform autonomous movement, including: extracting sweeper movement command data based on the sweeper trajectory data in the cooperative navigation path, and generating sweeper movement control data to represent the sweeper's direction of travel and step length based on the movement command data; extracting stair-climbing frame movement command data based on the stair-climbing frame trajectory data in the cooperative navigation path, and generating stair-climbing frame movement control data to represent the stair-climbing frame's direction of travel and step length based on the movement command data; and inputting the sweeper movement control data and the stair-climbing frame movement control data into the autonomous movement execution process to drive the sweeper and the stair-climbing frame to complete autonomous movement along their respective trajectory data and approach the target meeting point. Instruction Manual 2 / 15 Page 7 CN 121549721 A

[0014] Optionally, the robot vacuum cleaner and the stair-climbing frame are approached based on the cooperative navigation path, and docking status data reported by both parties are obtained during the approach to form docking action data, including: determining the target approach direction of the robot vacuum cleaner in the approach phase based on the robot vacuum cleaner trajectory data in the cooperative navigation path, and reporting robot vacuum cleaner approach status information to indicate the robot vacuum cleaner's posture change during the robot vacuum cleaner's movement along the target approach direction; determining the target approach direction of the stair-climbing frame in the approach phase based on the stair-climbing frame trajectory data in the cooperative navigation path, and reporting stair-climbing frame approach status information to indicate the stair-climbing frame's posture change during the stair-climbing frame's movement along the target approach direction; when the robot vacuum cleaner approach status information and the stair-climbing frame approach status information are both valid, generating alignment relationship data to indicate the real-time alignment relationship between the two parties based on their relative positional relationship; and constructing docking action data to describe the robot vacuum cleaner entering the stair-climbing frame's bearing area based on the alignment relationship data.

[0015] Optionally, when both the sweeper's approach status information and the stair-climbing frame's approach status information are valid, alignment relationship data representing the real-time alignment relationship between the two is generated based on their relative positional relationship. This includes: after acquiring the sweeper's approach status information, determining whether the sweeper's approach status information is valid based on a preset validity condition, and extracting sweeper approach posture parameters representing the sweeper's approach posture if valid; after acquiring the...After describing the approach status information of the stair-climbing frame, the validity of the approach status information is determined based on preset validity conditions. If valid, the approach posture parameters of the stair-climbing frame, representing the approach posture of the stair-climbing frame, are extracted. The preset validity conditions are set based on the numerical range and variation law corresponding to the approach status information of the sweeper and the stair-climbing frame, respectively, to determine whether the approach status information of the sweeper and the stair-climbing frame are in a valid state. Under the condition that both the approach posture parameters of the sweeper and the approach posture parameters of the stair-climbing frame are valid, the relative position offset and relative angle offset of the two are calculated, and alignment relationship data representing the real-time alignment relationship of the two is constructed based on the offsets.

[0016] Optionally, the docking action of the sweeper to the stair-climbing frame is completed based on the docking action data, and the floor switching operation of the sweeper is performed according to the target work area data, including: generating docking control data to constrain the sweeper to enter the carrying area of ​​the stair-climbing frame based on the docking action data, and generating docking completion confirmation information after the sweeper completes the entry action according to the docking control data; extracting target floor parameters based on the target work area data, and generating floor switching control data according to the target floor parameters; using the floor switching control data to drive the stair-climbing frame to perform the corresponding floor switching process, and releasing the sweeper after reaching the target floor.

[0017] Optionally, generating docking control data based on the docking action data to constrain the sweeper's entry into the load-bearing area of ​​the stair-climbing frame, and generating docking completion confirmation information after the sweeper completes the entry action according to the docking control data, includes: extracting docking posture parameters representing the sweeper's entry direction and alignment angle based on the docking action data, and generating docking trajectory control data to constrain the sweeper's movement trajectory according to the docking posture parameters; collecting load-bearing position detection information representing the sweeper's arrival at the load-bearing area during the sweeper's entry action according to the docking trajectory control data, and generating docking completion confirmation information when the load-bearing position detection information meets preset arrival conditions. A second aspect of this invention provides an intelligent summoning system for a robotic vacuum cleaner climbing a stair-climbing frame. The system includes: a triggering unit, configured to acquire summoning trigger information for triggering the robotic vacuum cleaner to dock with the stair-climbing frame, and generate location data including robotic vacuum cleaner positioning data and target work area data based on the summoning trigger information; and a path planning unit, configured to determine the movable area boundary of the robotic vacuum cleaner based on the positioning data in the location data, generate a target meeting point based on the location data of the target work area, construct a cooperative navigation path for the robotic vacuum cleaner to dock with the stair-climbing frame based on the area boundary and the target meeting point, and use the cooperative navigation path to drive the robotic vacuum cleaner and the stair-climbing frame to perform self-driving maneuvers.The main movement; the movement unit, used to perform the approach action between the sweeper and the stair-climbing frame based on the cooperative navigation path, and to acquire the docking status data reported by both parties during the approach process to form docking action data; the docking unit, used to complete the docking action of the sweeper to the stair-climbing frame based on the docking action data, and to perform the floor switching operation of the sweeper according to the target work area data. A third aspect of the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to execute the above-described intelligent summoning method for sweeper climbing stair-climbing frame.

[0018] A fourth aspect of the present invention provides an electronic device, the electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described intelligent summoning method for sweeper climbing stair-climbing frame.

[0019] A fifth aspect of the present invention provides a computer program product including a computer program that, when executed by a processor, implements the above-described intelligent summoning method for sweeper climbing stair-climbing frame.

[0020] Through the above technical solution, the present invention can establish a coherent cross-floor scheduling link in a multi-story residential environment, ensuring that the sweeping robot and the stair-climbing frame maintain consistent status information and path basis in key stages such as triggering, meeting, approaching, and docking. The system uses clear location data and target work area data to ensure that both parties converge around the same meeting point during movement, reducing disorientation or stagnation caused by environmental changes. The introduction of cooperative navigation paths eliminates the reliance on unidirectional searching, thereby improving the stability of the docking phase. The docking status data and docking action data generated during the approach process make the final entry and parking actions verifiable, avoiding the deviation or poor contact problems often seen in traditional solutions. After docking is completed, the entire process can directly connect to floor switching actions, forming a closed loop for cross-floor scheduling, thus meeting the user's continuous needs for automated cleaning in multiple scenarios.

[0021] Other features and advantages of the embodiments of the present invention will be described in detail in the following specific embodiments section.

[0022] The accompanying drawings are provided to further illustrate the embodiments of the present invention and constitute a part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the drawings: Figure 1 is a flowchart of the steps of an intelligent summoning method for a sweeping machine climbing a stair frame according to an embodiment of the present invention; Figure 2 is a general flowchart of the intelligent summoning method for a sweeping machine climbing a stair frame according to an embodiment of the present invention; Figure 3 is a detailed flowchart of the steps of autonomous triggering of a sweeping machine according to an embodiment of the present invention; Figure 4 is a detailed flowchart of the steps of user command triggering according to an embodiment of the present invention; Figure 5 is a flowchart of the close-range precision alignment stage between the sweeping machine and the stair frame according to an embodiment of the present invention.Intent; Figure 6 is a system structure diagram of the intelligent summoning system for a sweeper climbing a stair frame provided in one embodiment of the present invention; Figure 7 is a schematic diagram of the hardware and communication architecture of the implementation environment provided in one embodiment of the present invention. Detailed Embodiments

[0023] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the present invention and are not intended to limit the present invention.

[0024] Figure 1 is a flowchart of the steps of the intelligent summoning method for a sweeper climbing a stair frame provided in one embodiment of the present invention. As shown in Figure 1, the present invention provides an intelligent summoning method for a sweeper climbing a stair frame, the method including: Step S10: Obtain summoning trigger information for triggering the docking of the sweeper with the stair frame, and generate location data including sweeper positioning data and target work area data based on the summoning trigger information.

[0025] Specifically, the call trigger information used to trigger the docking of the sweeper with the stair-climbing frame is at least one of automatic trigger data reported by the sweeper and manual trigger data generated by user instructions. The automatic trigger data is generated based on the operating status information automatically reported by the sweeper when it completes the current cleaning task or receives onboard button instructions. The manual trigger data is generated based on the cross-floor movement instructions input by the user through a voice interaction terminal or mobile terminal.

[0026] Further, obtaining the sweeper's call trigger information and generating location data containing sweeper positioning data and target work area data based on the call trigger information includes: identifying the location reporting field in the call trigger information and extracting initial positioning information representing the sweeper's current spatial coordinates based on the location reporting field; parsing the task status field in the call trigger information and extracting initial call information representing the need for cross-floor movement based on the task status field; wherein, the task status field is a task status identifier field additionally recorded in the call trigger information to represent the sweeper's current task stage and cross-floor movement intention; constructing a joint data structure describing the sweeper's location attributes and call attributes based on the initial positioning information and the initial call information, and using this joint data structure as the location data.

[0027] Based on the present invention, the triggering stage establishes a unified task entry based on the "call trigger information". The call trigger information includes trigger information automatically reported by the sweeper and trigger information generated by user commands. Both types of triggering methods are converted into trigger expressions with the same structure after entering the parsing process. After parsing, corresponding "target work area data" is generated based on the trigger content. This data describes the target location of this cross-regional dispatch, such as the upper floor, lower floor, or...Crossing a semi-enclosed space with a threshold. To ensure a consistent spatial convergence target in the subsequent scheduling process, this invention uses the target work area as a common guide point for both the sweeping robot and the stair-climbing frame, so that both move towards the target area during the scheduling phase.

[0028] It should be noted that the sweeping robot, as an indoor robot, does not have all-terrain mobility capabilities, and its movement range is limited by the spatial layout of the current floor and its passable area. Therefore, in the path planning process, this invention first determines the movement boundary of the sweeping robot based on the indoor map, and then selects a local convergence path consistent with the direction of the target work area within the allowed range of the boundary, so that the sweeping robot can continue to approach the target work area without crossing its passable area. The stair-climbing frame moves from the passable main passage to the target area according to its own path structure. Through this mechanism of convergence of two entities towards the same target, the meeting time can be shortened without increasing the additional positioning complexity, and the overall efficiency of the summoning process can be improved.

[0029] In this embodiment of the invention, the triggering phase starts with the summoning trigger information. The summoning trigger information comes from two sources: one is actively reported by the robot vacuum during operation, reflecting the task status and spatial location; the other is input by the user via voice or mobile terminal, expressing a clear intention to move across floors. The two trigger paths converge to the same data entry point before entering the parsing process, ensuring the stable structure of subsequent logic.

[0030] Automatic trigger data comes from the robot vacuum's operating status report. After completing the cleaning task, the robot vacuum sends a data packet with a task completion identifier. The data packet contains fields such as task stage code, cleaning area number, and remaining action indication. Onboard button triggers also generate the same type of data packet. The parsing process directly reads the task stage code. If the code specification page 5 / 15 10 CN 121549721 A matches the cross-floor scheduling condition, the code is extracted as the trigger flag. Automatic trigger data has fixed field positions in its structure, which facilitates quick judgment in actual deployment.

[0031] Manual trigger data comes from user commands. After voice input is processed by the voice parsing module, a structured instruction text is generated. The text includes the target floor, the type of requested action, and the intention to connect. Mobile input directly generates similar structured content. The parsing process reads the floor number and task target based on the field labels and organizes these contents into a data structure with a fixed format. Natural language descriptions in the text, such as "next floor" or "upper floor," are mapped to standardized floor values ​​during the parsing stage. Manually triggered data has clear semantic boundaries and can be directly used as the scheduling entry point.

[0032] After the trigger data enters the parsing layer, it enters the location data construction process. This process extracts location data and target work area data from the call trigger information. The location data comes from the coordinate reporting field of the sweeping machine. The coordinate field usesThe format of x and y coordinates plus direction angle is used to read three values ​​at a fixed offset during parsing, and the validity is confirmed by range verification. Valid coordinate values ​​are directly used as the position of the sweeper in the current space for subsequent convergence point calculation.

[0033] The target work area data comes from the task status field. The task status field contains cross-floor requirement codes, which point to the target floor or the next task area. The parsing process converts them into target floor parameters according to the code table. If the trigger data comes from the user, the target work area data is provided by the user input field and written into the requirement structure in the same format. By unifying the data format, logical branches caused by differences in trigger sources can be avoided.

[0034] After completing the extraction of positioning data and target work area data, a joint data structure needs to be constructed. The joint data structure consists of two fixed parts: the position part records the sweeper coordinates and direction angle, and the requirement part records the target floor number and task target type. The two parts are written into the same data structure in the order of fixed fields to form the input data for path planning. This structure format is consistent throughout the entire process to ensure that the path planning stage does not rely on temporary field judgments.

[0035] The construction of the joint data structure brings a direct effect. The spatial attributes and task semantics of the robot vacuum cleaner are expressed in the same dataset, eliminating the need for multiple data indexing during the path planning process. Differences in the sources of trigger data are smoothed out at this stage, and path calculation can be performed in a unified format. Coordination and docking also function based on the same input logic because the location and demand data are fixed.

[0036] In engineering implementation, the core value of this stage is to reduce the impact of data sources on subsequent planning structures. After the location information and demand information are bound, the convergence point calculation, navigation planning, approach actions, and docking process can form a clear data flow. This data flow structure is more likely to remain stable in dynamic environments because each stage relies on the same data entry point, without requiring additional judgment based on trigger conditions.

[0037] In another possible implementation, the triggering stage adds a type of trigger data based on environmental state inference to address situations where the user has not actively issued instructions and the robot vacuum cleaner is not in a task-completed state. The core idea is to determine the necessity of cross-floor scheduling through environmental changes, so that the triggering mechanism no longer relies solely on explicit instructions. Environmental status information typically comes from low-power sensor nodes within the home, such as door magnetic switches, changes in floor lighting, and pyroelectric detectors at stairwells. Nodes report environmental frames at fixed intervals. Each environmental frame contains three fields: trigger tag, change amplitude, and duration. The parsing process determines whether a cross-floor requirement exists based on the combination of change amplitude and duration. For example, continuous passage events at a stairwell may indicate that a user is about to enter an upper-floor area.

[0038] When the parsing determines that the trigger condition is met, the parsing layer generates environmental trigger data. This data uses a method similar to...The trigger data has the same structural format, with fields including trigger source, recommended floor, and transition time window. The recommended floor is determined by the placement of environmental nodes, such as changes in lighting above stairs corresponding to the upper floors. The environmental trigger data is then written into the trigger entry along with the automatic and manual trigger data, ensuring that the three trigger paths maintain consistent subsequent processing logic.

[0039] This implementation adds an environmental inference module to the trigger link, enabling cross-floor scheduling to have a certain scene adaptability. It does not rely on user intervention, nor does it require the robot vacuum to be in a specific task phase, making it more user-friendly for multi-floor usage scenarios and providing a more timely input basis for the navigation and docking layers.

[0040] Step S20: Determine the movable area boundary of the sweeper based on the positioning data in the location data, generate a target meeting point based on the location data of the target work area data, construct a cooperative navigation path for the sweeper to meet the stair climbing frame based on the area boundary and the target meeting point, and use the cooperative navigation path to drive the sweeper and the stair climbing frame to perform autonomous movement respectively.

[0041] Specifically, the movable area boundary of the sweeping machine is determined based on the positioning data in the location data, and a target meeting point is generated based on the location data of the target work area data. A cooperative navigation path for the sweeping machine and the stair-climbing frame to meet is constructed based on the area boundary and the target meeting point. This includes: parsing the positioning data in the location data to obtain the current spatial orientation information of the sweeping machine, and determining area constraint data to represent the movable area boundary of the sweeping machine based on the spatial orientation information; parsing the location data of the target work area data to obtain target point information to represent the meeting target position, and generating a target meeting point to describe the meeting position of the sweeping machine and the stair-climbing frame based on the target point information; and constructing path description data to describe the respective movement trajectories of the sweeping machine and the stair-climbing frame based on the area constraint data and the target meeting point, thus forming the cooperative navigation path.

[0042] Further, based on the regional constraint data and the target meeting point, path description data is constructed to describe the respective movement trajectories of the sweeping robot and the stair-climbing frame, forming the cooperative navigation path. This includes: determining the boundary set of the sweeping robot's walkable area based on the regional constraint data, and extracting movement constraint parameters representing the sweeping robot's movement restrictions within the boundary set; determining the movement direction data of the stair-climbing frame from its current position to the target meeting point based on the target meeting point, and constructing accessibility parameters representing the stair-climbing frame's mobility accessibility; performing path planning calculations based on the movement constraint parameters and the accessibility parameters to generate sweeping robot trajectory data representing the sweeping robot's movement trajectory and stair-climbing frame trajectory data representing the stair-climbing frame's movement trajectory, respectively; and connecting the sweeping robot trajectory data with the stair-climbing frame's movement trajectory.The building frame trajectory data is combined into path description data.

[0043] Specifically, the collaborative navigation path is used to drive the sweeper and the stair-climbing frame to perform autonomous movement, including: extracting sweeper movement command data based on the sweeper trajectory data in the collaborative navigation path, and generating sweeper movement control data to represent the sweeper's direction of travel and step length based on the movement command data; extracting stair-climbing frame movement command data based on the stair-climbing frame trajectory data in the collaborative navigation path, and generating stair-climbing frame movement control data to represent the stair-climbing frame's direction of travel and step length based on the movement command data; inputting the sweeper movement control data and the stair-climbing frame movement control data into the autonomous movement execution process to drive the sweeper and the stair-climbing frame to complete autonomous movement along their respective trajectory data and approach the target meeting point.

[0044] In this embodiment of the invention, the triggering stage only provides the intent and location, while the navigation path truly pulls the sweeper and the stair-climbing frame into the same spatial logic. The process of constructing the path is more like organizing scattered information into an executable action framework. In engineering, this step often involves data segmentation, spatial constraint inference, and generation of target meeting points.

[0045] The entry point for path planning is location data. Location data includes two parts: positioning data and target work area data. The formats of both have been fixed in the previous stage, so they can be directly called in this stage without additional judgment. Positioning data gives the coordinates and orientation of the robot vacuum cleaner on the current floor. These values ​​can be used as the starting point for geometric calculations. Target work area data includes the target floor, docking stage, and calling purpose. It provides semantic clues to constrain the path trend. The two parts are combined to form the input pair for navigation planning.

[0046] The first step in path planning is to parse spatial orientation information from the positioning data. Coordinates are usually in x and y form, and the orientation angle is represented by a numerical value. During parsing, first check whether the coordinates are within the legal area of ​​the floor layout, and then confirm whether the orientation angle is within the valid range. The spatial orientation information of the robot vacuum cleaner often determines the approach direction, which is very important in the docking process. After parsing, area constraint data needs to be generated. The area constraint data describes the boundaries of the robot vacuum cleaner's movable area, including obstacle distribution, furniture obstruction, and spatial shape. During construction, it needs to be combined with an indoor map or local grid to mark impassable areas on the map, and then extract the coordinate set of the outer perimeter. The extracted boundary set can be used for subsequent derivation of movement constraint parameters.

[0047] In a specific implementation, the movement constraint parameters can be calculated based on the marked impassable areas and obstacle boundaries in the area constraint data. Specifically, firstly, a preliminary grid is constructed of the home environment based on the area constraint data.The system assigns a "passable" or "inaccessible" attribute to each location unit. Then, a boundary band corresponding to the obstacle boundary is extracted around each inaccessible unit to describe the robot's movement limitations when approaching obstacles. The range of the boundary band can be preset according to the robot's body shape and its walking stability requirements to ensure that edge collisions do not occur during the calculation process.

[0048] After completing the boundary marking, connectivity analysis is performed on the passability attributes of all grid units, dividing the independent passable areas into multiple walkable sub-regions. For each sub-region, its spatial extent, boundary shape, and connection exit location are extracted, and this information is mapped to a constraint set describing the robot's walkable range. Movement constraint parameters are further generated based on this constraint set, mainly used to characterize the robot's walkable range, executable turning range, and inaccessible path directions within the current area. As the basic input for path planning calculation, the movement constraint parameters enable the subsequently generated robot trajectory data to automatically avoid inaccessible areas and obstacle boundaries, thereby ensuring the executability of trajectory planning and environmental consistency.

[0049] The parsing path of the target work area data is relatively intuitive. The target work area data often contains target floor information, but the target point information of the current floor is mainly used in the navigation stage. For example, if the user wants the device to meet in the living room, or the device defaults to meeting in the center of the room after cleaning, these instructions will be written into the call request field. The parsing process reads the target point code from the request structure and finds the actual coordinates in the layout data of the current floor according to the code. After finding the coordinates, the target point information can be generated. The target point information serves as the basis for the subsequent construction of the target meeting point, and its accuracy directly affects the rationality of the docking position.

[0050] The generation of the target meeting point is usually based on the relative relationship between the target point information and the current position of the robot vacuum cleaner. The generation method is not complicated, but it needs to strictly follow the constraints of the passable area. If the target point is located in a narrow area or a densely furnished area, it needs to be fine-tuned according to the area constraint data. For example, if the target point is close to the table leg, the meeting point should be offset outward by a few units of coordinates to avoid making the path too narrow. The final target rendezvous point is a set of fixed coordinates, located both within the passable area and close to the docking point set by the user or task.

[0051] After obtaining the area constraint data and the target rendezvous point, path description data can be constructed. The path description data consists of two parts: one part describes the movement trajectory of the sweeping robot, and the other part describes the movement trajectory of the stair-climbing frame. The two trajectories have different starting points but the same ending point, and their movement methods are not entirely the same. The sweeping robot needs to select the shortest or most stable path within the passable area, while the stair-climbing frame may start from a fixed stopping point, and its path is more like a main line movement. The planning algorithm can use grid search, A*, Dijkstra, or simplified path calculation based on reachability masks, which takesThe specific implementation depends on the chosen algorithm. Regardless of the algorithm, the input parameters include regional constraint data, target meeting point, current coordinates, and environmental layout information. The output is two trajectory data sets, each containing a path point sequence and a direction sequence.

[0052] After the trajectory is generated, the two trajectories need to be combined into path description data. The path description data is a composite format that concatenates the sweeper trajectory data and the stair-climbing frame trajectory data in the order of the fields. The combined data structure maintains the independence of the trajectory specification page 8 / 15 13 CN 121549721 A, while facilitating logical scheduling during the movement phase. The path description data is relatively fixed in structure, including the number of trajectory points, the trajectory point sequence, the direction sequence, and the trajectory step length. The fixed structure ensures that it can be directly parsed during the autonomous movement phase without needing to perform format judgment.

[0053] With the path description data, the next step is to distribute the path to the two moving entities. The core of the distribution process is to convert the trajectory data into executable motion control data. The sweeper trajectory data contains the coordinates of the path points, so it is necessary to calculate the direction of travel and step length from the difference between adjacent coordinate points. The direction is represented in angle form, and the step length is represented in distance form. After conversion, the sweeper's movement control data is formed. The trajectory data of the stair-climbing frame is also converted in the same way to generate the stair-climbing frame's movement control data.

[0054] After the control data is formed, the execution stage can begin. The movement execution process reads the control data at fixed time slices and executes the movement commands step by step. The sweeper moves along the trajectory point sequence, and the stair-climbing frame moves from its starting position along the planned trajectory. The movement directions of the two do not need to be aligned at the same time, but both converge toward the target meeting point. During the movement execution process, it is necessary to monitor the coordinate deviation so that fine adjustments can be made when the deviation is large. The fine adjustment strategy usually adopts the method of calculating the error between the current position and the target path point and correcting the direction and step length by adjusting the ratio.

[0055] As the sweeper and the stair-climbing frame get closer, the meeting point generated in the path planning stage gradually comes into play. The meeting point provides a spatial anchor point, allowing the two to meet at a predictable location, rather than stopping at an uncontrollable dynamic location. The structure of the path description data ensures that the path recalculation does not need to be repeated in the movement stage, the execution logic is clear, and the process is stable.

[0056] In another possible implementation, the cooperative navigation path does not rely entirely on a single meeting point, but introduces a set of dynamic candidate meeting areas. This idea comes from the home environment with multiple rooms and obstacles, because fixed meeting points may not have good accessibility at certain times. The candidate meeting area consists of several spatial segments, each segment corresponding to a segment of observable accessibility data. When scanning these segments, it is necessary to combine the static layout of the map and recent movement records to determine whether there are local congestion or narrow areas caused by furniture movement.

[0057] The generation process of dynamic candidate meeting areas starts with location data. First, the location data of the robot vacuum cleaner is extracted.In the nearby open area, several candidate segments are divided by clustering. The center coordinates of each segment are used as temporary meeting points, and the segments are prioritized according to the target meaning in the target work area data. The sorting rules consider both geometric distance and recent traffic stability. Finally, the priority segment is selected as the new meeting point for constructing subsequent path description data.

[0058] The path planning stage will regenerate the trajectory based on the new meeting point. The trajectory of the sweeping robot needs to maintain smooth turning within the area covered by the candidate segments to avoid temporary stops in narrow areas. The path of the climbing frame is based on the main channel as the baseline and the direction is adjusted according to the accessibility parameter. When necessary, the planning layer can fine-tune the segment weights during the approach of the two main entities to allow the meeting target to move within a small range, so as to reduce the accumulation of deviations caused by environmental disturbances.

[0059] In a specific implementation, the accessibility parameter can be calculated based on the spatial connectivity relationship between the current position of the climbing frame and the target meeting point. Specifically, firstly, the environment of the floor where the stair-climbing frame is located is spatially discretized based on the regional constraint data, so that the floor structure, corridor direction, and stair entrance are all represented in the form of connected units. Starting from the current position of the stair-climbing frame, a layer-by-layer expansion search is performed on each connected unit to determine whether the stair-climbing frame can reach the target meeting point without violating environmental constraints. During the expansion search, paths containing obstacles, narrow passages, or areas with restricted turning are filtered out based on the accessibility markers between connected units to ensure the executability of the search results.

[0060] After obtaining the minimum connected path from the current position to the target meeting point, the path is further extracted, including the number of directional changes, path length, and possible turning points, and these spatial attributes are mapped to a set of parameters to describe the degree of accessibility. This set of parameters serves as the accessibility parameter, representing the feasibility and path complexity of the stair-climbing frame reaching the target meeting point under the current environmental structure. When a connected path does not exist, the reachability parameter is marked as unreachable to prompt the subsequent path planning module to adjust the target meeting point or replan the collaborative navigation path.

[0061] This implementation method, through the introduction of candidate meeting areas, ensures that path planning is no longer constrained by fixed points, and the scheduling chain can maintain continuity when faced with changes in furniture positions or partial blockages. For dynamic home environments, this mechanism is more likely to maintain the stability of the docking process and reduce the additional computational burden caused by multiple replannings.

[0062] Step S30: Based on the collaborative navigation path, the robot vacuum cleaner performs an approach action with the stair-climbing frame, and acquires the docking status data reported by both parties during the approach process to form docking action data.

[0063] Specifically, based on the robot vacuum cleaner trajectory data in the collaborative navigation path, the target of the robot vacuum cleaner in the approach phase is determined.The system identifies the approach direction and reports robot vacuum approach status information to indicate changes in robot vacuum posture as the robot moves along the target approach direction. Based on the stair-climbing frame trajectory data in the cooperative navigation path, the system determines the target approach direction of the stair-climbing frame during the approach phase and reports stair-climbing frame approach status information to indicate changes in stair-climbing frame posture as the stair-climbing frame moves along the target approach direction. When both the robot vacuum approach status information and the stair-climbing frame approach status information are valid, alignment relationship data is generated based on their relative positions to represent their real-time alignment relationship. Based on the alignment relationship data, docking action data describing the robot vacuum entering the stair-climbing frame's bearing area is constructed.

[0064] Further, when the sweeper's approach status information and the stair-climbing frame's approach status information are both valid, alignment relationship data representing the real-time alignment relationship between the two is generated based on their relative positional relationship, including: after acquiring the sweeper's approach status information, determining whether the sweeper's approach status information is valid based on a preset validity condition, and extracting sweeper approach posture parameters representing the sweeper's approach posture if valid; after acquiring the stair-climbing frame's approach status information, determining whether the stair-climbing frame's approach status information is valid based on a preset validity condition, and extracting stair-climbing frame approach posture parameters representing the stair-climbing frame's approach posture if valid; under the condition that both the sweeper's approach posture parameters and the stair-climbing frame's approach posture parameters are valid, calculating the relative position offset and relative angle offset between the two, and constructing alignment relationship data representing the real-time alignment relationship between the two based on the offset.

[0065] In one specific embodiment, the preset validity conditions are set based on the numerical range and change law corresponding to the sweeper's approach status information and the stair-climbing frame's approach status information, respectively. These conditions are used to determine whether the sweeper's approach status information and the stair-climbing frame's approach status information are in a valid state. After receiving the sweeper's approach status information, the position and attitude values ​​are checked against a range to confirm whether these values ​​fall within the expected range for normal operation of the equipment. When the position value exceeds the limit, the attitude value is incomplete, or the status field is missing, the approach status information is deemed invalid. Subsequently, the change law of the approach status information is further detected. If the position change between multiple consecutive frames of data jumps abnormally, the attitude change is discontinuous, or the update frequency is abnormal, the status information is also marked as invalid.

[0066] For the stair-climbing frame's approach status information, the same judgment process as for the sweeper is used, but the corresponding numerical range and change law are determined based on the stair-climbing frame's own motion characteristics. For example, the stair-climbing frame typically has a low attitude change rate and a relatively stable position change pattern. Therefore, when its attitude value fluctuates rapidly or its position changes...When the proximity status information is inconsistent with the mobility of the device, it will also be determined to be invalid. By using this judgment method that adapts to the two types of devices respectively, it can be ensured that all proximity status information entering the alignment relationship data calculation stage is in a reliable state.

[0067] In this embodiment of the invention, path planning can only provide a trend, while the proximity action needs to handle more local changes. It is more like breaking down a long path into a controllable end action, allowing the robot vacuum and the stair-climbing frame to gradually approach each other in a predictable area. The whole process relies on the trajectory data in the collaborative navigation path and the attitude information continuously reported during the movement. Only when the two parts are combined can a sufficiently stable alignment basis be generated.

[0068] The proximity action usually starts with the determination of the target direction. When the robot vacuum performs the proximity phase, it reads the last segment of the trajectory data, which is often composed of a set of direction vectors and step lengths. These data are regarded as the target proximity direction. The direction is relatively straightforward and is usually obtained based on the coordinate difference between adjacent path points. Once the direction is determined, the movement control will adjust the body posture according to the direction angle and advance with a shorter step size. During the advance, the approach status information will be reported periodically, mainly including horizontal displacement, angle change and body posture. Each field needs to be checked for boundaries to prevent outliers from entering subsequent calculations. The approach status information maintains a fixed format in structure to facilitate subsequent unified parsing.

[0069] The approach logic of the stair-climbing base is similar to that of the sweeping robot, but the trajectory planning method is slightly different. The path of the base is mostly along the main channel, the direction change is less than that of the sweeping robot, and the status information is more stable. After the trajectory data is parsed, the target approach direction is obtained, and then the movement is made with a fixed step size. During the movement, the approach status information of the stair-climbing base will be continuously reported. The field content is consistent with that of the sweeping robot, including horizontal displacement and angle offset. Due to the larger base structure, the sampling frequency of the status information is usually slightly lower, but it still meets the needs of alignment calculation.

[0070] Two state streams arrive at the parsing layer in parallel during the approach process. The primary task of the parsing layer is to determine whether the status information is valid. The validity check is performed based on preset conditions. Conditions generally include update cycle, offset range, and continuity of attitude change. If the state information meets the conditions, it is marked as valid, and the corresponding attitude parameters are extracted. The attitude parameters of the sweeping robot end consist of horizontal displacement, direction angle, and velocity change. The attitude parameter structure of the climbing frame end is consistent. The two sets of parameters are stored independently, waiting for subsequent alignment calculations.

[0071] The next step of alignment calculation will only start when both sets of attitude parameters are valid. The alignment calculation needs to handle the spatial difference between the two sides and express it in a relatively stable way. The basic idea of ​​the calculation is to transform the coordinates of both sides to the same coordinate system, and then calculate the position offset and angle offset. The position offset can be obtained directly through the coordinate difference, and the angle offset can be obtained through the coordinate difference.The degree offset can be obtained through the directional angle difference. The offset is smoothed once to reduce the impact of transient fluctuations in the sensor. The final alignment data includes the offset vector, angle difference, and relative direction. This set of data maintains fixed fields in structure to facilitate the generation of docking actions.

[0072] After the alignment data is constructed, the main task of the approach phase has been completed. The next step is to generate docking action data. The docking action data extracts the offset direction from the alignment data and performs coordinate transformation according to the spatial structure of the carrying area. The transformed parameters can describe the path trend of the sweeper entering the carrying area. The docking action data usually includes the entry angle, the target lateral offset, and the advance distance of the entry segment. The fields are arranged in a fixed order to facilitate quick access during the docking phase.

[0073] The implementation path of this stage does not rely on complex operators, but on a relatively stable data structure and a set of clear calculation rules. The sweeper end and the climbing frame end establish the approach direction through trajectory data, construct attitude parameters through status reporting, and then filter out abnormal values ​​through validity judgment. Finally, the two sets of attitude parameters are aligned under the same coordinate frame and then converted into executable docking action data.

[0074] Step S40: Based on the docking action data, the sweeper completes the docking action of the sweeper to the stair climbing frame, and performs the floor switching operation of the sweeper according to the target work area data.

[0075] Specifically, based on the docking action data, docking control data for constraining the sweeper to enter the carrying area of ​​the stair climbing frame is generated, and docking completion confirmation information is generated after the sweeper completes the entry action according to the docking control data; the target floor parameters are extracted based on the target work area data, and floor switching control data is generated according to the target floor parameters; the floor switching control data is used to drive the stair climbing frame to perform the corresponding floor switching process, and the sweeper is released after reaching the target floor.

[0076] Further, docking control data for constraining the sweeper's entry into the load-bearing area of ​​the stair-climbing frame is generated based on the docking action data, and docking completion confirmation information is generated after the sweeper completes the entry action according to the docking control data. This includes: extracting docking posture parameters representing the sweeper's entry direction and alignment angle based on the docking action data, and generating docking trajectory control data for constraining the sweeper's movement trajectory according to the docking posture parameters; collecting load-bearing position detection information representing the sweeper's arrival at the load-bearing area during the sweeper's entry action according to the docking trajectory control data, and generating docking completion confirmation information when the load-bearing position detection information meets preset arrival conditions.

[0077] In this embodiment of the invention, the docking action generally occurs after both trajectories converge to the merging area.The key task of this stage is to convert the alignment data from the previous stage into a set of executable entry constraints, allowing the sweeper to enter the load-bearing area of ​​the climbing frame in a relatively stable manner. The entire process is more like a piece of end-point control logic, which needs to handle direction, angle, and spatial offset simultaneously to keep the action coherent in the confined space.

[0078] The docking action data usually includes three types of parameters: entry direction, lateral offset, and target orientation. These parameters come from the alignment relationship of the previous stage, rather than simply relying on the path planning results. The entry direction is calculated based on the offset vector, which is generally derived from the direction difference from the meeting point to the entrance of the load-bearing area. The lateral offset reflects the degree of offset of the sweeper relative to the center line of the load-bearing area. This type of information helps to select a suitable entry angle. The target orientation provides a reference for the final docking posture. These parameters are integrated to form docking posture parameters, which serve as inputs for generating docking control data.

[0079] The process of generating docking control data is relatively straightforward, but it needs to be executed sequentially. The first step is to generate docking trajectory control data based on the docking posture parameters. This data structure contains multiple control commands, such as entry direction angle, advance step size, and angle correction magnitude. The azimuth angle is derived from the docking attitude parameters, and the propulsion step size is usually set to a short step mode to avoid overshoot at the entrance of the load-bearing area. The logic of angle correction mainly relies on the offset to reduce the path deviation caused by lateral offset. In this way, the sweeper has a more robust set of control rules before entering.

[0080] The second step is to collect load-bearing position detection information. During the execution of docking trajectory control data, it is necessary to continuously monitor the entry status of the sweeper. The detection information generally includes fields such as position deviation, leading edge distance, and height change. These fields help confirm whether the device has truly entered the effective range of the load-bearing area. The detection conditions usually adopt a set of preset arrival parameters, such as position error within a specified range, azimuth deviation less than a threshold, etc. When the detection information meets these conditions, docking completion confirmation information will be generated.

[0081] The role of docking completion confirmation information is to separate the approach stage and the floor switching stage. Only when the confirmation information is marked as valid will the control data related to floor switching be allowed to enter the next stage. This can avoid starting the climbing action when misaligned and reduce the potential risks caused by false triggering. The confirmation information generally consists of only one flag and one timestamp, used to record the completion status and time.

[0082] The floor switching logic typically begins by extracting target floor parameters from the target work area data. Target floor parameters are derived from the triggering phase, including the floor number input by the user or the floor number generated by the task requirements. After parsing, floor switching control data is generated. This control data contains the floor number, climbing direction, and movement step value, used to describe the basic structure of the cross-floor action. The generated control data follows a fixed field format for quick parsing by the mobile execution end.

[0083] Once the floor switching control data is ready, the cross-floor action enters the execution phase. The execution phase relies on the propulsion structure of the climbing frame, but the control logic is still read from the control data. The control data first gives the climbing direction, then the movement step, and finally uses the floor number as the stopping condition. The propulsion action continues to execute until the reference value of the target floor is scanned. The reference value may come from the floor marker, position sensor, or fixed height mapping. After the reference value is identified, the action enters the release phase.

[0084] The task of the release phase is relatively simple, that is, to guide the sweeper out of the carrying area. The release action is triggered by a short control command, and the sweeper moves from the carrying area to the preset position under the command. This position is usually a relatively open area, used to start the next cleaning task. The departure action also generates a status information to record whether the release behavior is completed normally.

[0085] This entire process binds the cross-floor action and the end docking action together. The docking control data ensures the stability of the posture during the entry action, the bearing position detection information provides the basis for arrival, the docking completion confirmation information forms a clear boundary, and the floor switching control data is responsible for connecting subsequent actions. The data structures of different stages are all processed in a unified format, so that the scheduling link presents a clear data flow. This structure is easier to maintain in a real home environment, especially in room layouts with more environmental disturbances, the whole process can respond more closely to real-time changes.

[0086] In a specific implementation, the cross-floor scheduling of the robot vacuum after completing the current task includes the following steps: 1) Trigger: After the robot vacuum completes all the cleaning tasks on the second floor, it automatically generates a request to call the stair climbing frame according to a preset program (e.g., the next step is to clean the third floor).

[0087] 2) Request: The robot vacuum sends a call request to the stair climbing frame through the home Wi-Fi network. The request includes the machine's current coordinates or the target that the stair climbing machine is expected to run to.

[0088] 3) Cooperative navigation: After receiving the request, the stair climbing frame uses LiDAR to navigate from its current position (e.g., the first stairwell) to the living room on the second floor. At the same time, the robot vacuum moves to an open area in the living room to wait.

[0089] 4) Precise mounting: After the stair-climbing frame enters the living room area, it captures the beacon signal through an infrared sensor and tracks it to within 1 meter; then it activates precision visual ranging and fine-tunes its own posture to align the platform docking rail with the sweeper. The sweeper drives onto the platform, confirming successful mounting.

[0090] 5) Transportation and release: The stair-climbing frame carries the sweeper up one floor to the third floor. After reaching a flat surface, the stair-climbing frame sends a release signal, and the sweeper drives off the platform to begin cleaning on the third floor.

[0091] In another possible specific implementation, the user's voice command summoning includes the following steps: 1) Trigger: The user says to the smart speaker in the living room: "Take the sweeper to the third floor to clean."2) Analysis and Distribution: The smart speaker uploads the voice to the cloud for semantic recognition, and analyzes the core actions as "summoning" and "delivery", with the target parameter being "third floor". The cloud server sends instructions to the robot vacuum (located in the second-floor bedroom) and the stair-climbing frame (located on the first floor) through the home gateway: "Go to the second-floor bedroom to dock, and transport to the third floor after successful docking".

[0092] 3) Collaborative Navigation: After receiving the instructions, the robot vacuum moves to the center of the bedroom to wait and sends a guidance signal. The stair-climbing frame navigates to the center of the bedroom.

[0093] 4) Loading and Execution: After both parties complete the precise loading, the stair-climbing frame carries the robot vacuum up one floor to the third floor. The stair-climbing frame sends an "arrival" signal, and the robot vacuum drives off the platform to start the cleaning task on the third floor.

[0094] Preferably, when the robot vacuum finishes cleaning or needs to be charged, it can summon the stair-climbing frame again to send it back to the original floor or the floor leading to the charging dock.

[0095] As shown in Figure 2, in a specific implementation, the smart summoning method can be executed according to two types of triggering processes. The first is the robot vacuum's side triggering process. After completing the current cleaning task, the robot vacuum generates a task command and sends it to the stair climber via a communication link. Upon receiving the task command, the stair climber parses the task content and activates its movement control module, moving itself to the target location corresponding to the task command. Once the stair climber reaches the target location, it sends a completion notification to the robot vacuum, allowing the robot vacuum to continue to the next task. The second is the stair climber's side triggering process. After receiving a task command from the user terminal (page 13 / 15 of the user manual, 18 CN 121549721 A), the stair climber directly responds to the task command and moves to the designated location. After the task is completed, the stair climber also sends a completion notification to the robot vacuum, ensuring consistency in the collaborative process between the two. Through these dual-trigger processes, a unified collaborative scheduling mechanism can be maintained under different task sources.

[0096] Correspondingly, as shown in Figure 3, if the sweeper is triggered autonomously, when the sweeper determines in advance or immediately during the cleaning process that it needs to perform up and down stairs, the sweeper will generate a corresponding task instruction based on its own task status and send it to the stair climber. After receiving the task instruction, the stair climber parses the target location information and then starts the movement module to move to the designated location. When the stair climber reaches the target location, it will send a notification to the sweeper that the task has been completed. After receiving the notification, the sweeper will enter the docking process after the current task is completed, realizing the up and down stairs scheduling process under autonomous triggering.

[0097] Correspondingly, as shown in Figure 4, if the sweeper is triggered by a user instruction, when the user issues an operation instruction to summon the stair climber through the APP, the sweeper will first receive the APP instruction and parse the target floor and summoning request information. Subsequently, the sweeper generates a corresponding stair climber task instruction and sends it to the stair climber. After receiving the task instruction, the stair climber starts the movement control module.The robot vacuum moves to the designated location and sends a message of completion to the robot vacuum upon arrival. The robot vacuum then synchronizes the result to the app, allowing the user to know the task completion status in real time, thus completing the summoning process triggered by the user's command.

[0098] In a specific implementation, as shown in Figure 5, after completing the collaborative navigation phase, the robot vacuum and the stair-climbing frame enter a close-range precision alignment phase. This phase mainly handles any remaining positional and angular deviations that may exist during the approach process, ensuring the stability and consistency of the final docking action. Specifically, when the robot vacuum first navigates to its corresponding target point A, it actively sends arrival information to the stair-climbing frame, enabling the stair-climbing frame to synchronously initiate its approach process. Upon receiving this information, the stair-climbing frame navigates to target point B according to the docking position requirements in the task command, or directly enters the docking preparation state when both machines are within close range.

[0099] After the stair-climbing frame reaches the target point B, it will send an approach prompt message to the sweeping machine via a short-range communication link, causing the sweeping machine to begin the action of "searching for the stair-climbing frame signal". When scanning the surrounding environment, the sweeping machine will determine the approximate location of the stair-climbing frame based on the signal strength, direction changes, and its own positioning changes, and will feed back the identified stair-climbing frame location information to the stair-climbing frame end. After receiving the feedback signal, the stair-climbing frame will perform fine-tuning actions based on the location clues provided by the sweeping machine, so that the positional relationship between the two gradually tends to overlap.

[0100] After both parties have obtained valid position signals, the system will determine whether the two parties have met the docking conditions based on the stability and trend of the signals. When the determination result is that docking is possible, the sweeping machine and the stair-climbing frame will drive the platform to finally approach each other according to their respective docking strategies, so that the sweeping machine can smoothly slide into the carrying area or docking slot of the stair-climbing frame. After docking is completed, the sweeping machine end will enter a stopped state, while the stair-climbing frame end will enter the subsequent task execution process, such as moving across floors or resetting the position.

[0101] Figure 5 is a system structure diagram of an intelligent summoning system for a sweeper climbing a stair frame provided in an embodiment of the present invention. As shown in Figure 5, an embodiment of the present invention provides an intelligent summoning system for a sweeper climbing a stair frame, the system comprising: a triggering unit, configured to acquire summoning trigger information for triggering the docking of the sweeper and the stair frame, and generate location data including sweeper positioning data and target work area data based on the summoning trigger information; a path planning unit, configured to construct a collaborative navigation path for the sweeper and the stair frame to meet based on the location data, and use the collaborative navigation path to drive the sweeper and the stair frame to perform autonomous movement respectively; a movement unit, configured to perform an approach action between the sweeper and the stair frame based on the collaborative navigation path, and acquire docking status data reported by both parties during the approach process to form docking action data; and a docking unit, configured to complete the docking action of the sweeper to the stair frame based on the docking action data, and based on...The floor switching operation of the sweeper is performed according to the target work area data. (Instruction manual, pages 14 / 15, 19 CN 121549721 A)

[0102] In a specific embodiment, the hardware and communication architecture of the implementation environment of the intelligent summoning system of the sweeper climbing the stair frame is shown in Figure 7. The stair frame and the sweeper are each equipped with a built-in WiFi module and can achieve bidirectional communication through a local area network. The sweeper also maintains a network connection with the server to receive user instructions from the smart terminal APP or report task status. The smart terminal interacts indirectly with the sweeper and the stair frame through the server, thereby forming a complete intelligent summoning control link. A third aspect of the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to execute the above-described intelligent summoning method of the sweeper climbing the stair frame.

[0103] A fourth aspect of the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described intelligent summoning method of the sweeper climbing the stair frame.

[0104] A fifth aspect of the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements the above-described intelligent summoning method for a sweeping robot climbing a stair frame.

[0105] Those skilled in the art will understand that all or part of the steps in the methods described in the above embodiments can be implemented by a program instructing related hardware. The program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0106] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the various possible combinations will not be described separately in the embodiments of the present invention.

[0107] Furthermore, various different embodiments of the present invention can be arbitrarily combined, as long as they do not violate the present invention.The ideas behind the embodiments of the invention should also be considered as the content disclosed in the embodiments of the present invention. Instruction Manual 15 / 15 Page 20 CN 121549721 A Figure 1 Figure 2 Instruction Manual Appendix 1 / 5 Page 21 CN 121549721 A Figure 3 Instruction Manual Appendix 2 / 5 Page 22 CN 121549721 A Figure 4 Instruction Manual Appendix 3 / 5 Page 23 CN 121549721 A Figure 5 Instruction Manual Appendix 4 / 5 Page 24 CN 121549721 A Figure 6 Figure 7 Instruction Manual Appendix 5 / 5 Page 25 CN 121549721 A Abstract Abdominal ultrasound examination method, system and device INTELLIGENT CALLING METHOD AND SYSTEM FOR STAIR-CLIMBING BASE FRAME OF SWEEPER Abstract Embodiments of the present invention provide an intelligent calling method and system for a stair-climbing base frame of a sweeper, and belong to the technical field of intelligent mobile cleaning equipment. The method includes: acquiring calling trigger information for triggering docking between the sweeper and the stair-climbing base frame, and generating position data containing sweeper positioning data and target working area data based on the calling trigger information; constructing a cooperative navigation path for the sweeper to rendezvous with the stair-climbing base framebased on the position data, and separately driving the sweeper and the stair-climbing base frame to perform autonomous movement through the cooperative navigation path; executing an approaching action between the sweeper and the stair-climbing base frame according to the cooperative navigation path, and acquiring docking state data reported by both parties during the approaching process to form docking action data; completing the docking of the sweeper with the stair-climbing base frame based on the docking action data, and performing floor switching operation of the sweeper according to the target working area data. The solution of the present invention realizes stable, continuous and correctable cooperative scheduling of the sweeper and the stair-climbing base frame in a multi-floor environment.

Claims

1. A method for intelligently summoning a sweeping robot's stair-climbing frame, characterized in that, The method includes: Obtain the call trigger information used to trigger the docking of the sweeper with the stair-climbing frame, and generate location data containing sweeper positioning data and target work area data based on the call trigger information; The movable area boundary of the sweeper is determined based on the positioning data in the location data, and a target meeting point is generated based on the location data of the target work area data. A cooperative navigation path for the sweeper to meet the stair climbing frame is constructed based on the area boundary and the target meeting point, and the cooperative navigation path is used to drive the sweeper and the stair climbing frame to perform autonomous movement. Based on the cooperative navigation path, the robot vacuum cleaner performs an approach action with the stair-climbing frame, and acquires the docking status data reported by both parties during the approach process to form docking action data; Based on the docking action data, the sweeper completes the docking action with the stair-climbing frame, and performs the floor switching operation of the sweeper according to the target work area data.

2. The method according to claim 1, characterized in that, The call trigger information used to initiate the docking of the sweeper with the stair-climbing frame is at least one of the following: automatically triggered data reported by the sweeper and manually triggered data generated by user commands. The automatic trigger data is generated based on the operating status information automatically reported by the sweeper when it completes the current cleaning task or receives onboard button commands; Based on the cross-floor movement command input by the user through a voice interaction terminal or mobile terminal, the command information to be parsed is generated, and the manual trigger data is generated according to the command information to be parsed.

3. The method according to claim 1, characterized in that, Obtain the call trigger information of the robot vacuum cleaner, and generate location data including robot vacuum cleaner positioning data and target work area data based on the call trigger information, including: Identify the location reporting field in the summoning trigger information, and extract the initial positioning information representing the current spatial coordinates of the robot vacuum cleaner based on the location reporting field; The task status field in the summoning trigger information is parsed, and the initial summoning information representing the need for cross-floor movement is extracted based on the task status field; wherein, The task status field is a task status identifier field that is additionally recorded in the summoning trigger information to indicate the current task stage and cross-floor movement intention of the robot vacuum. Based on the initial positioning information and the initial summoning information, a joint data structure is constructed to describe the location attributes and summoning attributes of the robot vacuum cleaner, and this joint data structure is used as the location data.

4. The method according to claim 1, characterized in that, Based on the positioning data in the location data, the movable area boundary of the sweeper is determined, and a target rendezvous point is generated based on the location data of the target work area. A cooperative navigation path for the sweeper to rendezvous with the stair-climbing frame is constructed based on the area boundary and the target rendezvous point, including: The positioning data in the location data is parsed to obtain the current spatial orientation information of the sweeping machine, and the regional constraint data used to represent the boundary of the sweeping machine's movable area is determined based on the spatial orientation information; The location data of the target work area is parsed to obtain target point information representing the convergence target location, and a target convergence point describing the convergence location of the sweeper and the stair climbing frame is generated based on the target point information; Based on the regional constraint data and the target meeting point, path description data is constructed to describe the respective movement trajectories of the sweeping robot and the stair-climbing frame, thus forming the cooperative navigation path.

5. The method according to claim 4, characterized in that, Based on the regional constraint data and the target meeting point, path description data is constructed to describe the respective movement trajectories of the sweeping robot and the stair-climbing frame, forming the cooperative navigation path, including: Based on the aforementioned regional constraint data, a boundary set of the sweeper's traversable area is determined, and movement constraint parameters representing the sweeper's movement restrictions are extracted from this boundary set; wherein... The movement constraint parameters are calculated based on the marked impassable areas and obstacle boundaries in the area constraint data; Based on the target meeting point, the movement direction data of the stair-climbing frame from its current position to the target meeting point is determined, and accessibility parameters representing the mobility accessibility of the stair-climbing frame are constructed; wherein, The accessibility parameter is calculated based on the spatial connectivity between the current position of the stair-climbing frame and the target meeting point; Based on the movement constraint parameters and the reachability parameters, path planning calculations are performed to generate sweeper trajectory data representing the sweeper's movement trajectory and stair climbing frame trajectory data representing the stair climbing frame's movement trajectory, respectively. The sweeper trajectory data and the stair-climbing frame trajectory data are combined to form path description data.

6. The method according to claim 4, characterized in that, The cooperative navigation paths are used to drive the sweeping robot and the stair-climbing frame to perform autonomous movement, including: Based on the robot vacuum's trajectory data in the cooperative navigation path, robot vacuum movement command data is extracted, and robot vacuum movement control data representing the robot vacuum's direction of travel and travel distance is generated based on the movement command data. Based on the stair-climbing frame trajectory data in the cooperative navigation path, the stair-climbing frame movement command data is extracted, and stair-climbing frame movement control data representing the direction and length of the stair-climbing frame is generated according to the movement command data; The sweeper's movement control data and the stair-climbing frame's movement control data are respectively input into the autonomous movement execution process to drive the sweeper and the stair-climbing frame to complete autonomous movement along their respective trajectory data and approach the target meeting point.

7. The method according to claim 1, characterized in that, Based on the cooperative navigation path, the robot vacuum cleaner performs an approach maneuver with the stair-climbing frame, and acquires docking status data reported by both parties during the approach process to form docking action data, including: Based on the robot vacuum's trajectory data in the cooperative navigation path, the target approach direction of the robot vacuum during the approach phase is determined, and the robot vacuum's approach status information, which indicates the robot vacuum's attitude change, is reported during the robot vacuum's movement along the target approach direction. Based on the trajectory data of the climbing frame in the cooperative navigation path, the target approach direction of the climbing frame is determined during the approach phase, and the climbing frame approach status information, which is used to indicate the attitude change of the climbing frame, is reported during the movement of the climbing frame along the target approach direction. When both the sweeper's proximity status information and the stair-climbing frame's proximity status information are valid, alignment relationship data representing the real-time alignment relationship between the two is generated based on their relative positional relationship. Based on the alignment relationship data, docking action data is constructed to describe the sweeper's movement into the load-bearing area of ​​the stair-climbing frame.

8. The method according to claim 7, characterized in that, When both the sweeper's proximity status information and the stair-climbing frame's proximity status information are valid, alignment relationship data representing their real-time alignment is generated based on their relative positional relationship, including: After obtaining the robot vacuum's approach status information, the robot vacuum's approach status information is determined to be valid based on a preset validity condition. If it is valid, the robot vacuum's approach posture parameters, which represent the robot vacuum's approach posture, are extracted. After acquiring the approach status information of the climbing frame, the validity of the approach status information is determined based on preset validity conditions. If valid, the approach posture parameters of the climbing frame, representing the approach posture of the climbing frame, are extracted. The preset validity conditions are set based on the numerical range and variation law of the sweeper's approach status information and the stair climbing frame's approach status information, respectively, and are used to determine whether the sweeper's approach status information and the stair climbing frame's approach status information are in a valid state. Under the condition that the approach posture parameters of the sweeper and the approach posture parameters of the climbing frame are both valid, the relative position offset and relative angle offset of the two are calculated, and the alignment relationship data representing the real-time alignment relationship of the two are constructed based on the offset.

9. The method according to claim 1, characterized in that, Based on the docking action data, the sweeper completes the docking action with the stair-climbing frame, and performs the floor switching operation of the sweeper according to the target work area data, including: Based on the docking action data, docking control data is generated to constrain the sweeper from entering the load-bearing area of ​​the stair climbing frame, and docking completion confirmation information is generated after the sweeper completes the entry action according to the docking control data. Target floor parameters are extracted based on the target work area data, and floor switching control data is generated based on the target floor parameters; The floor switching control data is used to drive the stair-climbing frame to perform the corresponding floor switching process, and the sweeper is released after reaching the target floor.

10. The method according to claim 9, characterized in that, Based on the docking action data, docking control data is generated to constrain the sweeper's entry into the support area of ​​the stair-climbing frame. After the sweeper completes the entry action according to the docking control data, docking completion confirmation information is generated, including: Based on the docking action data, docking posture parameters are extracted to represent the sweeper's driving direction and alignment angle, and docking trajectory control data for constraining the sweeper's movement trajectory is generated according to the docking posture parameters. During the process of the sweeper performing the driving action according to the docking trajectory control data, load position detection information is collected to indicate the position of the sweeper when it arrives at the load area, and docking completion confirmation information is generated when the load position detection information meets the preset arrival conditions.

11. An intelligent summoning system for a sweeping robot's stair-climbing base, characterized in that, The system includes: The triggering unit is used to acquire call trigger information for triggering the docking of the sweeper with the stair climbing frame, and to generate location data containing sweeper positioning data and target work area data based on the call trigger information; The path planning unit is used to determine the movable area boundary of the sweeping machine based on the positioning data in the location data, generate a target meeting point based on the location data of the target work area data, construct a cooperative navigation path for the sweeping machine to meet the stair climbing frame based on the area boundary and the target meeting point, and use the cooperative navigation path to drive the sweeping machine and the stair climbing frame to perform autonomous movement respectively. The mobile unit is used to perform the approach action between the sweeping robot and the climbing frame based on the cooperative navigation path, and to acquire the docking status data reported by both parties during the approach process to form docking action data; The docking unit is used to complete the docking action of the sweeper to the stair climbing frame based on the docking action data, and to perform the floor switching operation of the sweeper according to the target work area data.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the intelligent summoning method for the sweeper climbing the stair frame as described in any one of claims 1-10.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the intelligent summoning method for the sweeper climbing the stair frame as described in any one of claims 1-10.

14. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the intelligent summoning method for the sweeper climbing the stair frame according to any one of claims 1-10.

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