Mobile robot, and collaborative control method and architecture therefor

Abstract

A mobile robot, and a collaborative control method and architecture therefor, which are used for realizing dual / multi-robot collaborative transportation of goods. The method comprises: using robots and goods as a rigid body, and determining a virtual geometric center of the rigid body (S1); on the basis of transportation task data and sensor data of the robots, calculating motion instruction data of the virtual geometric center of the rigid body (S2); on the basis of the current motion instruction data of the virtual geometric center, acquiring current motion instruction data which respectively corresponds to the robots (S3); and sending the motion instruction data of the robots to the corresponding robots by means of real-time communication, such that the robots perform collaborative motion on the basis of the respective motion instruction data (S5). The collaborative control method for robots can improve the collaborative control effect and performance of mobile robots during a collaborative operation.

Description

A mobile robot and its collaborative control method and architecture Technical Field

[0001] The present invention relates to the field of mobile robot control technology, and in particular to a mobile robot and a collaborative control method and architecture thereof. Background Art

[0002] In the field of smart manufacturing, intelligent robots are replacing human labor and even some mechanical equipment in the production process. In manufacturing scenarios, large equipment often needs to be moved, installed, or adjusted within the factory. Traditionally, this is accomplished using gantry cranes and transport trucks within the workshop. This traditional method, with its numerous operational steps, poor flexibility, and low safety, is no longer suitable for the requirements of intelligent and digital production. Therefore, a safer, more flexible, and intelligent method is needed.

[0003] The operating method represented by intelligent mobile robots provides a new possibility for the intelligent and digital realization of this type of production link.

[0004] Collaborative operation of two or more mobile robots is a recently developed solution centered around intelligent robots. Under collaborative control, two or more mobile robots perform operations on the same target object, such as transporting it. However, even if each robot is controlled independently based on a unified collaborative control strategy and uses the same mobile robot body model, differences in actual control performance can still occur. Large differences can cause the robots performing the collaborative operation to experience significant additional stress or external forces. For example, when jointly supporting a target object for transport, differences in robot control performance can generate horizontal forces between the robots and the target object, affecting the final transport operation and even causing the operation to fail. To address the performance inconsistencies caused by differences in control performance during collaborative operation of two or more robots, a new technical solution is necessary to implement real-time control within the robot control system and ensure that this real-time performance is synchronized between the two or more robots. This provides the prerequisite for collaborative control and ensures synchronized control performance between the robots. Summary of the Invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present invention provides a mobile robot and a collaborative control method and architecture thereof to improve the collaborative control effect and performance of dual / multiple mobile robots during collaborative operation.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a collaborative control method for mobile robots, which is applied to a first robot and at least one second robot collaboratively transporting cargo, wherein the method comprises the first robot performing the following steps:

[0008] Treat the first robot, the second robot, and the cargo as a rigid body, and determine a virtual geometric center of the rigid body;

[0009] Calculating current motion instruction data of the virtual geometric center based on the received transfer task data, the sensor data of the first robot itself, and the sensor data of the second robot;

[0010] Calculating the current motion instruction data corresponding to the first robot and the second robot based on the current motion instruction data of the virtual geometric center;

[0011] The motion instruction data currently corresponding to the second robot is transmitted to the corresponding second robot, so that the second robot and the first robot can perform coordinated motion according to the motion instruction data currently corresponding to each of them.

[0012] Furthermore, the cycles of internal control, internal data transmission, and external data transmission performed by the first robot and the second robot are the same or are integer multiples of each other, and are based on the same clock signal.

[0013] Furthermore, the first robot receives sensor data of the second robot through the first communication module;

[0014] The first robot transmits the motion instruction data currently corresponding to the second robot to the corresponding second robot through the first communication module, or through the first communication module and the second communication module;

[0015] The first communication module is a Zigbee communication module, and the second communication module is a WIFI communication module.

[0016] Furthermore, the calculating of the current motion instruction data of the virtual geometric center based on the received transfer task data, the sensor data of the first robot itself, and the sensor data of the second robot includes:

[0017] Calculating actual trajectory data of the virtual geometric center based on sensor data of the first robot and sensor data of the second robot;

[0018] Calculating expected trajectory data of the virtual geometric center based on the transfer task data and actual trajectory data of the virtual geometric center;

[0019] Based on the expected trajectory data of the virtual geometric center, current motion instruction data of the virtual geometric center is calculated.

[0020] Furthermore, the calculating the actual trajectory data of the virtual geometric center based on the sensor data of the first robot and the sensor data of the second robot includes:

[0021] Calculating actual motion data of the first robot and the second robot based on the sensor data of the first robot and the sensor data of the second robot;

[0022] Calculating actual motion data of the virtual geometric center based on actual motion data of the first robot and the second robot;

[0023] Based on the actual motion data of the virtual geometric center, actual trajectory data of the virtual geometric center is calculated.

[0024] Furthermore, the calculating the actual motion data of the virtual geometric center based on the actual motion data of the first robot and the second robot includes:

[0025] Based on a pre-established transformation matrix, inversely transform the actual motion data of the first robot and the second robot to obtain the actual motion data of the virtual geometric center;

[0026] The calculating, based on the current motion instruction data of the virtual geometric center, the current motion instruction data corresponding to the first robot and the second robot respectively includes:

[0027] Based on the conversion matrix, the current motion instruction data of the virtual geometric center is converted to decompose the current motion instruction data of the virtual geometric center into motion instruction data currently corresponding to the first robot and the second robot.

[0028] Furthermore, the first robot simultaneously transmits the motion instruction data currently corresponding to the second robot to the corresponding second robot through the first communication module and the second communication module. The method further includes executing the following data fusion step by the second robot:

[0029] Determining whether the time stamps and position stamps corresponding to the motion instruction data from the first communication module and the second communication module match;

[0030] If any one of the timestamp and the position stamp matches, the matched motion instruction data is fused and the fused result is used as the final motion instruction data; if neither the timestamp nor the position stamp matches, the motion instruction data from the second communication module is discarded and the motion instruction data from the first communication module is used as the final motion instruction data; or,

[0031] If both the timestamp and the position stamp match, the matching motion instruction data will be fused, and the fused result will be used as the final motion instruction data. If either the timestamp or the position stamp does not match, the motion instruction data from the second communication module will be discarded, and the motion instruction data from the first communication module will be used as the final motion instruction data.

[0032] In second aspect, the present invention provides a mobile robot, which is the first robot or the second robot that implements the collaborative control method as described above, and the robot includes a robot body, a driving wheel arranged at the bottom of the robot body, and a carrying platform arranged at the top of the robot body and used to carry the cargo.

[0033] Furthermore, the mobile robot is a differential drive robot;

[0034] The carrying platform is configured to be actively rotatable or passively rotatable on the robot body; and / or

[0035] The bearing platform is a jacking structure or a non-jacking structure.

[0036] In a third aspect, the present invention provides a collaborative control architecture for mobile robots, the architecture comprising a first robot and at least one second robot that collaborate to transport cargo, wherein the first robot, the second robot, and the cargo serve as a rigid body;

[0037] The first robot calculates current motion instruction data of the virtual geometric center of the rigid body based on the transfer task data, the sensor data of the first robot itself, and the sensor data of the second robot, and decomposes the current motion instruction data of the virtual geometric center into current motion instruction data corresponding to the first robot and the second robot respectively;

[0038] The second robot and the first robot perform coordinated movement according to the currently corresponding movement instruction data.

[0039] Furthermore, the first robot is also used for:

[0040] Calculating actual trajectory data of the first robot and the second robot based on sensor data of the first robot and the second robot;

[0041] Calculating an expected motion trajectory of the virtual geometric center based on the transfer task data and actual trajectory data of the first robot and the second robot;

[0042] Calculating trajectory instruction data for the first robot and the second robot based on the expected motion trajectory of the virtual geometric center, so that the second robot and the first robot perform coordinated motion according to the currently corresponding motion instruction data and the trajectory instruction data;

[0043] The first robot also calculates the error change value between the motion trajectory instruction data corresponding to the first robot and the second robot and the actual motion trajectory data within a previous predetermined time interval, and based on the corresponding error change value, corrects the motion trajectory instruction data corresponding to the first robot and the second robot respectively.

[0044] Furthermore, the first robot and the second robot are respectively equipped with a wheel hub motor driven by a corresponding servo driver, and a motion control unit correspondingly connected to the servo driver;

[0045] The motion control units of the first robot and the second robot control the operation of the corresponding servo drivers according to the currently corresponding motion instruction data, so that the first robot and the second robot can synchronously perform coordinated motion according to the currently corresponding motion instruction data.

[0046] Furthermore, the motion control units of the first robot and the second robot send the corresponding motion instruction data to the corresponding servo drivers once every first predetermined period T0;

[0047] The first robot sends the corresponding motion instruction data to its own motion control unit once every second predetermined period T1 through the control data channel;

[0048] The first robot sends the corresponding motion instruction data to the first communication module once every third predetermined period T2 through the control data channel, so as to transmit the corresponding motion instruction data to the corresponding second robot through the first communication module;

[0049] The working cycle of the first communication module is a fourth predetermined cycle T3, and the internal control cycle of the servo driver is a fifth predetermined cycle Tc;

[0050] Among them, the first predetermined period T0, the second predetermined period T1, the third predetermined period T2, the fourth predetermined period T3, and the fifth predetermined period Tc are equal to or are integer multiples of each other; and the control data channel, the first communication module, and the motion control unit use the same clock signal.

[0051] By adopting the above technical solution, the present invention has the following beneficial effects:

[0052] The present invention treats each robot and cargo as a rigid body. Based on the sensor data of each robot, the current motion instruction data of the rigid body's virtual geometric center is calculated. The current motion instruction data of the virtual geometric center is then decomposed into the motion instruction data corresponding to the first robot and the second robot respectively, and the data is distributed in real time. This achieves real-time closed-loop control of each robot and maintains real-time synchronization between the collaborative robots, providing a prerequisite for collaborative control, thereby improving the collaborative control effect and performance of mobile robots during collaborative operation. In addition, the use of Zigbee to transmit the main motion control data and sensor data further ensures real-time performance. The internal control, data transmission, and external communication data transmission of each robot maintain a unified rhythm, that is, the clock signal is unified and the data update cycle is the same or an integer multiple, which further ensures the collaborative control effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] FIG1 is a schematic diagram of the collaborative operation of mobile robots in the present invention;

[0054] FIG2 is a schematic structural diagram of the mobile robot of the present invention;

[0055] FIG3 is a top view of the mobile robot of the present invention;

[0056] FIG4 is a flow chart showing system motion parameters and control of a mobile robot according to the present invention;

[0057] FIG5 is a flow chart of a collaborative control method for a mobile robot according to the present invention;

[0058] FIG6 is a schematic diagram of the control process of the collaborative control method of the mobile robot in the present invention;

[0059] FIG7 is a schematic diagram of the data fusion processing method adopted by the present invention;

[0060] FIG8 is a diagram of a collaborative control architecture of a mobile robot according to the present invention. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0062] The terms used in this disclosure are for the purpose of describing particular embodiments only and are not intended to be limiting.

[0063] This disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0064] As shown in FIG1 , the present invention uses two or more (two shown in the figure) mobile robots (hereinafter referred to as robots) 1 and 2 to work together to jointly carry the same cargo 3 and complete automatic navigation and transfer operations, thereby realizing fully intelligent and fully digital control operations.

[0065] In the present invention, the robot that ranks first in the forward direction can be called the first robot 1, and the remaining robots can be called the second robot 2. Each robot 1 and 2 has the same physical structure and internal control architecture. The difference is that in addition to controlling its own movement, the first robot 1 also plays the role of the leading robot, and the movement instructions of the goods 3 must be issued by the first robot 1. Although the second robot 2 has the same control architecture and the same capabilities, as the other party in the collaborative operation, it does not take the task of actively controlling the overall transportation of the goods 3, and only receives instructions from the first robot 1 and instructions from the robot scheduling system or two-way communication. It should be noted that the present invention does not limit the position of the first robot 1, and the first robot 1 and the second robot 2 can be interchangeable.

[0066] The structure of each mobile robot for collaborative operation according to the present invention is shown in Figures 2 and 3 . Specifically, it includes a robot body 11, drive wheels 12 disposed at the bottom of the robot body 11, and a support platform 13 disposed at the top of the robot body 11. The robot body 11 is also equipped with a first communication module 14 (such as a Zigbee communication module) for data exchange with other robots, and a second communication module 15 (such as a WiFi communication module, or a WiFi / 5G communication module integrating WiFi and 5G) for data exchange with the robot scheduling system and other robots. Motion data (including command data and sensor data) between two or more robots is primarily transmitted via Zigbee; other data is primarily transmitted via WiFi; and motion data is primarily transmitted via Zigbee. This primarily leverages the high reliability and ease of real-time implementation of this communication method to achieve real-time motion control data exchange between the two or more robots, thereby ensuring real-time and synchronized motion control.

[0067] It should be understood that the drive wheels 12 can rotate forward (forward), reverse (backward), or turn under the control of the robot controller. In one embodiment, as shown in Figure 3, the mobile robot employs four drive wheels 12 to accommodate heavy load handling. The mobile robot is preferably a differential drive robot, meaning that the left and right drive wheels 12 are differentially driven. The two left drive wheels 12 are controlled by the same control signal and can be considered to have the same real-time rotation speed, rotation angle, and acceleration / deceleration. The two right drive wheels 12 are controlled by another identical control signal and can also be considered to have the same real-time rotation speed, rotation angle, and acceleration / deceleration.

[0068] In an operative manner, only the front two wheels may be driving wheels, and the rear two wheels may be passive wheels. It should be understood that when all four wheels are driving wheels, it helps to enhance the mobility of the robot when carrying heavier cargo 3.

[0069] In the present invention, the load platform 13, used to support the cargo 3, can be designed as a passively driven structure (i.e., it can rotate freely and passively within the horizontal plane under the action of an external force). Alternatively, it can be designed as an actively driven structure, i.e., it can be driven by a motor and gears and rotated under the control of a robot controller. The load platform 13 can be designed as an active lifting structure or a non-lifting structure. A lifting structure can be raised or lowered to raise or lower the cargo 3.

[0070] When the load-bearing cooperative mobile robot based on differential drive wheels of the present invention carries cargo 3, since the load-bearing platform thereon is a rotatable structure (either active rotation or passive rotation), under the action of cooperative control, the cargo 3 can be moved in any direction with high flexibility, thereby realizing U-turn and rotation operations in a small space.

[0071] The present invention regards each robot 1, 2 and cargo 3 as a rigid body, takes the speed, steering angle, etc. of the virtual geometric center of the rigid body as the investigation target, and completes the collaborative operation tasks of automatic navigation, automatic posture adjustment, and autonomous walking based on the perception sensors integrated on each robot body.

[0072] The virtual geometric center of the rigid body is the symmetrical point of the center of each robot. For the dual-robot collaborative operation shown in Figure 1, the midpoint C between the centers A and B of the two robots 1 and 2 is taken as the virtual geometric center of the rigid body. The movement indicators of the entire cargo 3 are evaluated by parameters such as the speed and angle of point C. That is, during the collaborative control process, the movement of point C represents the movement of the entire cargo.

[0073] In Figure 1, steering angle θ1 is the angle between the direction of travel of robot 1 and a line perpendicular to the line connecting the centers of the two robots. Steering angle θ2 is the angle between the direction of travel of robot 2 and a line perpendicular to the line connecting the centers of the two robots. Steering angle θc is the angle between the direction of movement of midpoint C and a line perpendicular to the line connecting the centers of the two robots. When robots 1 and 2 are under coordinated control, θ1 and θ2 can be the same or different.

[0074] When carrying cargo 3, robots 1 and 2 can rotate around point A and point B respectively (at this time, the left wheel and the right wheel rotate in opposite directions).

[0075] In order to achieve coordinated control of two or more mobile robots, when a first robot 1 is determined to be the "leading" robot, a control computing unit is integrated into the first robot 1 to provide a coordinated control method for the mobile robots, as shown in Figures 4-6. The method includes the following steps:

[0076] S1, the first robot 1, the second robot 2 and the cargo 3 are regarded as a rigid body, and the virtual geometric center of the rigid body is determined.

[0077] As mentioned above, the virtual geometric center of the rigid body is the symmetrical point of the center of each robot. For the dual-robot collaborative operation shown in Figure 1, the midpoint C between the centers A and B of the two robots 1 and 2 is taken as the virtual geometric center of the rigid body.

[0078] S2, based on the received transfer task data, the sensor data of the first robot 1 itself and the sensor data of the second robot 2, calculate the current motion instruction data (also called motion instruction parameters) of the virtual geometric center point C.

[0079] Specifically, the sensor data of first robot 1 and second robot 2 comes from their respective integrated perception sensors. Second robot 2's sensor data is transmitted to first robot 1 via the aforementioned first communication module (Zigbee). Due to the high reliability and real-time nature of Zigbee communication, real-time data exchange between the two or more robots is possible, ensuring real-time and synchronized motion control.

[0080] The transfer task data may, for example, include the starting address, target address, transfer route trajectory, related status, etc. of the virtual geometric center point C, which is usually issued by the robot dispatching center. The first robot 1 communicates with the robot dispatching center through the second communication module (WIFI / 5G) to receive the transfer task data issued by the robot dispatching center.

[0081] Step S2 is specifically calculated by the following steps S21 and S22:

[0082] S21 , calculating actual trajectory data of the virtual geometric center point C based on the sensor data of the first robot 1 and the sensor data of the second robot 2 .

[0083] Step S21 calculates the actual trajectory data of the virtual geometric center point C through the following steps:

[0084] S211: Calculate actual motion data of the first robot 1 and the second robot 2 based on the sensor data of the first robot 1 and the sensor data of the second robot 2. The actual motion data of the first robot 1 includes the actual linear velocity V1, actual angular velocity ω1, and actual steering angle θ1 of the first robot 1 (represented by point A); the actual motion data of the second robot 2 includes the actual linear velocity V2, actual angular velocity ω2, and actual steering angle θ2 of the second robot 2 (represented by point B).

[0085] S212: Calculate the actual motion data of the virtual geometric center, point C, based on the actual motion data of the first robot 1 and the second robot 2. Specifically, the actual motion data of point C can be inversely transformed based on a pre-established transformation matrix to obtain the actual motion data of point C, including the actual linear velocity Vc, actual angular velocity ωc, and actual steering angle θc of point C. This transformation matrix is ​​a matrix established by treating all robots 1, 2, and the cargo 3 as a single rigid body. It represents the coordinate transformation relationship between the kinematic model of the cargo 3 (point C) and the first robot 1 (point A) and the second robot 2 (point B).

[0086] S213 , calculating actual trajectory data of point C based on the actual motion data of the virtual geometric center point C, including the actual position and actual posture (angle) of point C.

[0087] S22, calculating the current motion instruction data of the virtual geometric center point C based on the received transfer task data and the actual trajectory data of the virtual geometric center point C.

[0088] Specifically, the desired trajectory of virtual geometric center C is first calculated based on the received transfer task data and the actual trajectory data of virtual geometric center C. Then, the current motion command data for virtual geometric center C is calculated based on the desired trajectory data. The motion command data for virtual geometric center C includes the target linear velocity Vc', target angular velocity ωc', and target steering angle θc' for the desired movement of cargo 3 (i.e., point C).

[0089] S3 , based on the current motion instruction data of the virtual geometric center point C, obtain the current motion instruction data corresponding to the first robot 1 and the second robot 2 .

[0090] Specifically, based on the pre-established conversion matrix, the current motion command data (Vc', ωc', and θc') at point C is converted to decompose the current motion command data into motion command data corresponding to first robot 1 and second robot 2. The motion command data corresponding to first robot 1 includes the target linear velocity V1', target angular velocity ω1', and target steering angle θ1' for first robot 1. The motion command data corresponding to second robot 2 includes the target linear velocity V2', target angular velocity ω2', and target steering angle θ2' for second robot 2.

[0091] S5, transmitting the motion instruction data currently corresponding to the second robot 2 to the corresponding second robot 2 in real time, so that the first robot 1 and the second robot 2 synchronously perform coordinated motion according to their respective currently corresponding motion instruction data.

[0092] Specifically, the first robot 1 can transmit the corresponding motion instruction data to the corresponding second robot 2 in real time through the first communication module 14, or can simultaneously transmit the corresponding motion instruction data to the corresponding second robot 2 in real time through the first communication module 14 and the second communication module 15. Thus, while the first robot 1 moves according to its corresponding motion instruction data, the second robot 2 can also move synchronously according to its corresponding motion instruction data, thereby achieving coordinated control of the robots 1 and 2.

[0093] In Robot 1 and Robot 2, closed-loop control of the action behavior based on the above data is executed respectively, and synchronous control is achieved to ensure the synchronization and accuracy of the actions between the two robots.

[0094] As described above, robot 1 generates motion commands for the virtual geometric center, point C. At this point, point C serves as the virtual leader of the two robots, while robots 1 and 2 serve as followers. The sensor data provided by the two robots serves as sensor data for the virtual geometric center, C. Robot 2's sensor data is transmitted to robot 1 via Zigbee communication. This data is then used to generate motion command data for point C, which is then decomposed into motion command data for robots 1 and 2 using a transformation matrix. This motion command data (i.e., motion control commands) is then transmitted to robot 2 via Zigbee communication, while trajectory command data is sent to robot 2 via Wi-Fi communication. Simultaneously, robot 2 transmits its trajectory data to the robot dispatch center via Wi-Fi / 5G, as shown in Figure 5.

[0095] Zigbee communication has high reliability, but the transmission data bandwidth is low. Therefore, it is only used to transmit sensor data and motion control parameters in the present invention.

[0096] In the present invention, data related to collaborative control between the first robot 1 and the second robot 2 is communicated via Zigbee communication, leveraging the technology's high reliability, robustness, and short latency to ensure the real-time and reliable collaborative control between the robots. Furthermore, due to the relatively limited data bandwidth of Zigbee, as previously mentioned, each robot is also integrated with a second communication module (e.g., a Wi-Fi communication module) to facilitate other data exchange (e.g., with the robot dispatch center).

[0097] The above steps can realize real-time closed-loop control of each collaborative robot. This real-time performance maintains real-time synchronization between the collaborative robots, providing a prerequisite for collaborative control, thereby ensuring the synchronous control performance between the collaborative robots.

[0098] It should be understood that the aforementioned control computing unit can also be integrated into the second robot 2 of the present invention, but when it is not serving as the "leading" robot, the control computing unit integrated in the second robot 2 does not work.

[0099] In addition, the first robot 1 and the second robot 2 of the present invention are each equipped with an in-wheel motor for driving the corresponding drive wheel. The in-wheel motor is driven by a corresponding servo drive, which is controlled by a corresponding motion control unit. The robot's control computing unit and motion control unit can be integrated into the same robot controller, or each can be separately provided in a separate robot controller. After the first robot 1 obtains the current motion instruction data corresponding to itself and the second robot 2, it transmits its own corresponding motion instruction data to its own motion control unit, and transmits the current motion instruction data corresponding to the second robot 2 to the corresponding motion control unit of the second robot 2 in real time, so that the motion control units of the first robot 1 and the second robot 2 can synchronously control the operation of the corresponding servo drive according to their respective corresponding motion instruction data. This enables the first robot 1 and the second robot 2 to synchronously move according to their respective current motion instruction data, thereby achieving coordinated control between the robots.

[0100] In the present invention, the motion control unit of each robot and the corresponding servo driver exchange data using an industrial communication bus, such as CanOpen, EtherCat, etc. In order to ensure synchronous real-time control effects, the industrial communication buses used by different robots are based on the same heart rate, so that the control inside each servo driver can achieve synchronous real-time matching. As shown in Figure 6, the motion control unit of each robot 1 and 2 sends corresponding motion instruction data to the corresponding servo driver once every first predetermined period T0. The control calculation unit of the first robot 1 sends corresponding motion instruction data to the motion control unit of the first robot once every second predetermined period T1 through the control data channel. The control calculation unit of the first robot 1 sends corresponding motion instruction data to the first communication module (i.e., Zigbee communication module) once every third predetermined period T2 through the control data channel, so that the corresponding motion instruction data is transmitted to the corresponding second robot 2 through the first communication module.

[0101] In the present invention, the heartbeat cycle of the first communication module is the fourth predetermined cycle T3, and the internal control cycle of the servo driver is the fifth predetermined cycle T c Among them, the first predetermined period T0, the second predetermined period T1, the third predetermined period T2, the fourth predetermined period T3, the fifth predetermined period T cThe data exchange mode with equal time intervals achieves time controllability and predictability of control data interaction, thus achieving a high degree of real-time and deterministic performance. The control data channel, the first communication module, and the motion control unit use the same clock signal.

[0102] As can be seen, in the present invention, the cycles for internal control, internal data transmission, and external data transmission by the first and second robots are identical or integer multiples of each other, and are based on the same clock signal. That is, the robot controller's internal control cycle, data transmission, and external communication data transmission have a unified rhythm (the data update cycle is aligned). Since some links do not necessarily have the same short time period, they can be set to integer multiples of the time period. This ensures that all data flows, whether control flow or sensor data flow, are time-controlled and predictable. This is a real-time measure, thus ensuring coordinated control.

[0103] The control flow shown in Figure 6 demonstrates the same internal control structure for both robots. Zigbee communication, which allows for timed data exchange, executes the control cycle and data transmission between the two robots, ensuring synchronization between them. This ensures synchronized control within and between the two robots, encompassing the physical control process, control loops, and control parameter transmission timing. This approach offers low latency, strong time predictability, and a stable control rhythm, laying the foundation for high-performance dual-robot collaborative control.

[0104] In one feasible method, motion parameter data is also transmitted via WIFI communication; this transmission is carried out between two robots, and also between the robot and the scheduling system. The robot and the scheduling system can also be transmitted via 5G communication. How to obtain the final motion data of the robot and exchange the data with the scheduling system is also an issue to be considered in the present invention.

[0105] Specifically, the present invention adopts the data fusion processing method shown in Figure 7. When the first robot simultaneously sends the current corresponding motion instruction data of the second robot through the first communication module (Zigbee) and the second communication module (WIFI), the second robot determines whether the timestamp and position stamp (the position stamp refers to the contained spatial position coordinate data) corresponding to the motion instruction data of the second robot from the first communication module and the second communication module match, and performs fusion processing based on the judgment result.

[0106] In one embodiment, if either the timestamp or the position stamp matches, the data under the two communication modes are considered to be the same data, and a preset data fusion algorithm is used to fuse the matching motion instruction data, and the fusion result is used as the final motion instruction data of the second robot; if both the timestamp and the position stamp do not match, the motion instruction data from the second communication module is discarded, and the motion instruction data from the first communication module is used as the final motion instruction data of the second robot. The final motion instruction data can be fed back to the robot dispatch center via the WIFI / 5G communication module.

[0107] In another embodiment, if both the timestamp and the position stamp match, the matched motion instruction data are fused, and the fused result is used as the final motion instruction data of the second robot. If either the timestamp or the position stamp does not match, the motion instruction data from the second communication module is discarded, and the motion instruction data from the first communication module is used as the final motion instruction data of the second robot. The final motion instruction data can be fed back to the robot dispatch center via the WIFI / 5G communication module.

[0108] The resulting data processed by the above method is multidimensional data, which serves as the robot's final result data for data exchange with the scheduling system. This method of motion data fusion processing improves the reliability and accuracy of robot motion data transmission and processing, overcoming issues such as incomplete data, data disconnection, and packet loss caused by unreliable Wi-Fi and other communication methods. This ensures that the dual collaborative robots have high operational reliability and collaboration.

[0109] As shown in FIG8 , the present invention also provides a collaborative control architecture for mobile robots, which adopts a kinematic model based on a virtual geometric center point C. The desired motion trajectory of the point (i.e., trajectory instruction data) is used as input, and the output is decomposed into the desired motion trajectory of the first robot 1 and the second robot 2 through coordinate system transformation. The desired motion trajectory is compared with the actual motion trajectory of the corresponding robot to obtain the difference, i.e., the trajectory error. The trajectory error is calculated based on the time period T=N*(T c +T0+T1+T2+T3), in order to examine the time interval, the error change value of two adjacent time periods is calculated, and the error change value is compensated into the trajectory instruction data of robot 1 and robot 2 respectively, thereby forming dynamic compensation control.

[0110] Specifically, the collaborative control architecture of the present invention includes a first robot and at least one second robot that collaboratively transport the virtual geometric center, and the first robot, the second robot and the cargo are regarded as a rigid body; wherein, the first robot calculates the current motion instruction data of the virtual geometric center point C based on the transport task data, the sensor data of the first robot itself and the sensor data of the second robot; and then calculates the current corresponding motion instruction data of the first robot 1 and the second robot 2 based on the current motion instruction data of point C in the virtual geometry; the second robot and the first robot synchronously perform collaborative movement according to the current corresponding motion instruction data.

[0111] In the collaborative control architecture, as shown in FIG8 , the first robot can also calculate the actual trajectory data of each of the first and second robots based on their sensor data; then calculate the trajectory instruction data of the virtual geometric center based on the transfer task data and the actual trajectory data of each of the first and second robots; and then calculate the trajectory instruction data of each of the first and second robots based on the expected motion trajectory of the virtual geometric center (the trajectory instruction data is also the expected motion trajectory, and is specifically calculated here based on the kinematic model and coordinate transformation of the virtual geometric center). The trajectory instruction data can be sent to the second robot simultaneously with the motion instruction data (given the bandwidth limitations of Zigbee and the large amount of trajectory data, the real-time requirements are relatively low, so the trajectory data is transmitted using WiFi, see FIG5 ), so that the second robot and the first robot can perform collaborative motion based on their respective corresponding motion instruction data and trajectory instruction data.

[0112] The first robot can also obtain the previous predetermined time length T (for example, T=N*(T0+T1+T2+T3+T c ), where N is a positive integer, the error change between the trajectory command data corresponding to the first robot and the second robot and the actual trajectory data is calculated. Based on the corresponding error change, the trajectory command data corresponding to the first robot and the second robot are respectively corrected, as shown in Figure 8. This forms dynamic compensation control and ultimately achieves collaborative control of the robots.

[0113] Although specific embodiments of the present invention have been described above, those skilled in the art will appreciate that these are merely illustrative and that the scope of protection of the present invention is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, and such changes and modifications shall fall within the scope of protection of the present invention.

Claims

1. A collaborative control method for a mobile robot, applied to a first robot and at least one second robot collaboratively transporting goods, characterized in that: The method performs the following steps by the first robot: Taking the first robot, the second robot and the cargo as a rigid body, determining the virtual geometric center of the rigid body; Calculate current motion instruction data of the virtual geometric center based on the received transfer task data, the sensor data of the first robot itself, and the sensor data of the second robot; Based on the current motion instruction data of the virtual geometric center, calculating the current motion instruction data corresponding to the first robot and the second robot respectively; The motion instruction data currently corresponding to the second robot is transmitted to the corresponding second robot, so that the second robot and the first robot can perform coordinated motion according to the motion instruction data currently corresponding to each other.

2. The collaborative control method according to claim 1, characterized in that: The cycles of internal control, internal data transmission, and external data transmission performed by the first robot and the second robot are the same or in integer multiples and are based on the same clock signal.

3. The collaborative control method according to claim 1, characterized in that: The first robot receives sensor data of the second robot through the first communication module; The first robot transmits the motion instruction data currently corresponding to the second robot to the corresponding second robot through the first communication module, or through the first communication module and the second communication module; The first communication module is a Zigbee communication module, and the second communication module is a WIFI communication module.

4. The collaborative control method according to claim 1, characterized in that: The calculating the current motion instruction data of the virtual geometric center based on the received transfer task data, the sensor data of the first robot itself and the sensor data of the second robot includes: Calculating actual trajectory data of the virtual geometric center based on the sensor data of the first robot and the sensor data of the second robot; Calculating expected trajectory data of the virtual geometric center based on the transfer task data and actual trajectory data of the virtual geometric center; Based on the expected trajectory data of the virtual geometric center, current motion instruction data of the virtual geometric center is calculated.

5. The collaborative control method according to claim 4, characterized in that: The calculating the actual trajectory data of the virtual geometric center based on the sensor data of the first robot and the sensor data of the second robot includes: Calculating actual motion data of the first robot and the second robot based on the sensor data of the first robot and the sensor data of the second robot; Calculating actual motion data of the virtual geometric center based on actual motion data of the first robot and the second robot; Based on the actual motion data of the virtual geometric center, actual trajectory data of the virtual geometric center is calculated.

6. The collaborative control method according to claim 5, characterized in that: The calculating the actual motion data of the virtual geometric center based on the actual motion data of the first robot and the second robot includes: Based on a pre-established transformation matrix, inversely transform the actual motion data of the first robot and the second robot to obtain the actual motion data of the virtual geometric center; The calculating, based on the current motion instruction data of the virtual geometric center, the current motion instruction data corresponding to the first robot and the second robot respectively includes: Based on the conversion matrix, the current motion instruction data of the virtual geometric center is converted to decompose the current motion instruction data of the virtual geometric center into motion instruction data currently corresponding to the first robot and the second robot respectively.

7. The collaborative control method according to claim 1, characterized in that: The first robot transmits the motion instruction data currently corresponding to the second robot to the corresponding second robot simultaneously through the first communication module and the second communication module, and the method further includes executing the following data fusion step through the second robot: Determine whether the timestamp and the position stamp corresponding to the motion instruction data from the first communication module and the second communication module match; If any one of the timestamp and the position stamp matches, the matching motion instruction data is fused, and the fused result is used as the final motion instruction data; if neither the timestamp nor the position stamp matches, the motion instruction data from the second communication module is discarded, and the motion instruction data from the first communication module is used as the final motion instruction data; or, If both the timestamp and the position stamp match, the matching motion instruction data will be fused and the fused result will be used as the final motion instruction data. If either the timestamp or the position stamp does not match, the motion instruction data from the second communication module will be discarded and the motion instruction data from the first communication module will be used as the final motion instruction data.

8. A mobile robot, characterized in that: The mobile robot is a first robot or a second robot that implements the collaborative control method as described in any one of claims 1 to 7, and the robot includes a robot body, driving wheels arranged at the bottom of the robot body, and a carrying platform arranged at the top of the robot body and used to carry the cargo.

9. The mobile robot according to claim 8, characterized in that: The mobile robot is a differential drive robot; The carrying platform is configured to be actively rotatable or passively rotatable on the robot body; and / or The bearing platform is a jacking structure or a non-jacking structure.

10. A collaborative control architecture for a mobile robot, characterized in that: The architecture includes a first robot and at least one second robot that cooperate in transporting cargo, wherein the first robot, the second robot and the cargo act as a rigid body; The first robot calculates the current motion instruction data of the virtual geometric center of the rigid body based on the transfer task data, the sensor data of the first robot itself and the sensor data of the second robot, and decomposes the current motion instruction data of the virtual geometric center into the motion instruction data currently corresponding to the first robot and the second robot respectively; The second robot and the first robot perform coordinated movement according to the motion instruction data currently corresponding to each other.

11. The collaborative control architecture according to claim 10, wherein: The first robot is also used for: Calculating actual trajectory data of the first robot and the second robot based on sensor data of the first robot and the second robot; Calculating the expected motion trajectory of the virtual geometric center based on the transfer task data and actual trajectory data of the first robot and the second robot; Based on the expected motion trajectory of the virtual geometric center, calculating the trajectory instruction data of the first robot and the second robot respectively, so that the second robot and the first robot perform coordinated motion according to the motion instruction data and the trajectory instruction data currently corresponding to each other; The first robot also calculates the error change value between the trajectory instruction data corresponding to the first robot and the second robot and the actual trajectory data within the previous predetermined time interval, and based on the corresponding error change value, corrects the trajectory instruction data currently corresponding to the first robot and the second robot respectively.

12. The collaborative control architecture according to claim 10, wherein: The first robot and the second robot are also respectively equipped with a wheel hub motor driven by a corresponding servo driver, and a motion control unit correspondingly connected to the servo driver; The motion control units of the first robot and the second robot control the operation of the corresponding servo drivers according to the motion instruction data currently corresponding to each other, so that the first robot and the second robot can synchronously perform coordinated motion according to the motion instruction data currently corresponding to each other.

13. The collaborative control architecture according to claim 12, wherein: The motion control units of the first robot and the second robot send the corresponding motion instruction data to the corresponding servo drivers once every first predetermined period T0; The first robot sends the corresponding motion instruction data to the motion control unit of the first robot once every second predetermined period T1 through the control data channel; The first robot sends the corresponding motion instruction data to the first communication module once every third predetermined period T2 through the control data channel, so as to transmit the corresponding motion instruction data to the corresponding second robot through the first communication module; The working cycle of the first communication module is the fourth predetermined cycle T3, and the internal control cycle of the servo driver is the fifth predetermined cycle T c ; The first predetermined period T0, the second predetermined period T1, the third predetermined period T2, the fourth predetermined period T3, the fifth predetermined period T c are equal or are integer multiples of each other; and the control data channel, the first communication module, and the motion control unit use the same clock signal.

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