Motion control method and device, computer equipment and storage medium

Abstract

The invention provides a motion control method and device, computer equipment and a storage medium. The method comprises the following steps: determining a current task stage of a robot in a process of executing a navigation task by the robot; according to the current task stage, a target motion mode is determined, the navigation task comprises a plurality of task stages, each task stage corresponds to a different motion mode, and the different motion modes have precision differences; and controlling the robot to move according to the target motion mode. According to the method, the problem that high precision and high efficiency cannot be considered when the robot executes the navigation task in the prior art can be solved, and the adaptability of the robot to the navigation tasks with different precision requirements is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of robotics, and in particular to motion control methods, devices, computer equipment, and storage media. Background Art

[0002] With the increasing popularity and application of robotics technology, robots have become an integral part of human society, driving innovation and development in industries such as industry, services, and healthcare. With the continuous advancement and innovation of technology, robots will continue to play an important role and bring more convenience and well-being to humanity.

[0003] In related technologies, robots often experience low accuracy or low efficiency when performing navigation tasks. In one case, improving navigation efficiency reduces accuracy, resulting in poor performance. In another case, improving accuracy reduces efficiency, resulting in longer navigation times. Summary of the Invention

[0004] To overcome the problems existing in the related art, the present disclosure provides a motion control method, apparatus, computer equipment and storage medium.

[0005] According to a first aspect of the embodiments of the present disclosure, the present application provides a motion control method, the method comprising:

[0006] During the process of the robot performing the navigation task, determining the current task phase of the robot;

[0007] Determining a target motion mode according to the current mission stage, wherein the navigation mission includes multiple mission stages, each mission stage corresponds to a different motion mode, and there are differences in accuracy between different motion modes;

[0008] The robot is controlled to move according to the target motion pattern.

[0009] In combination with any of the disclosed embodiments, controlling the robot to move according to the target motion pattern includes:

[0010] determining a target accuracy of the target motion pattern according to the target motion pattern;

[0011] In response to the target accuracy being no greater than a preset accuracy threshold, controlling the robot to move according to a mission navigation map and target environment data collected by at least one sensor;

[0012] In response to the target accuracy being greater than the preset accuracy threshold, the robot is controlled to move according to target environment data collected by at least one sensor.

[0013] In combination with any of the disclosed embodiments, controlling the robot to move according to the target motion pattern includes:

[0014] Acquire target environment data collected by a target sensor combination corresponding to the target motion mode, wherein different motion modes correspond to different sensor combinations, different sensor combinations have different accuracy, and the accuracy of the motion mode is positively correlated with the accuracy of the sensor combination;

[0015] The robot is controlled to move according to the target environment data.

[0016] In combination with any of the disclosed embodiments, the step of obtaining target environment data collected by the target sensor combination corresponding to the target motion pattern includes:

[0017] Obtaining environmental data collected by each sensor in the target sensor combination corresponding to the target motion pattern;

[0018] Each environmental data is fused based on the preset weight of each sensor to obtain target environmental data.

[0019] In combination with any of the disclosed embodiments, the fusing of each environmental data based on the preset weight of each sensor to obtain target environmental data includes:

[0020] Performing coordinate transformation on at least one environmental data to unify the coordinate system of each environmental data;

[0021] Each environmental data is fused based on the preset weight of each sensor to obtain target environmental data.

[0022] In combination with any of the disclosed embodiments, controlling the robot to move according to the target motion pattern includes:

[0023] Determining a target motion speed of the robot according to the target motion mode, wherein different motion modes correspond to different motion speeds, and the accuracy of the motion mode is negatively correlated with the motion speed;

[0024] The robot is controlled to move based on the target movement speed.

[0025] In combination with any of the disclosed embodiments, controlling the robot to move according to the target motion pattern includes:

[0026] Determining a target distance threshold according to a target motion mode, wherein different motion modes correspond to different distance thresholds, and the accuracy of the motion mode is negatively correlated with the distance threshold;

[0027] In response to the distance between the robot and the target position of the current task stage being less than the target distance threshold, controlling the robot to stop moving. In conjunction with any of the disclosed embodiments, in response to the current task stage being the last task stage in the navigation task, the method further includes:

[0028] determining a target location of the navigation task based on target environment data collected by at least one sensor;

[0029] The target position and target posture of the current task phase are determined according to the target position of the navigation task and the task content of the navigation task.

[0030] In a second aspect, the present application further provides a motion control device, comprising:

[0031] a stage determination module, configured to determine a current task stage of the robot during the robot's execution of a navigation task;

[0032] a mode determination module, configured to determine a target motion mode according to the current mission stage, wherein the navigation mission includes multiple mission stages, each mission stage corresponds to a different motion mode, and there are differences in accuracy between different motion modes;

[0033] A motion control module is used to control the robot to move according to the target motion mode.

[0034] In one embodiment, the motion control module is specifically configured to:

[0035] determining a target accuracy of the target motion pattern according to the target motion pattern;

[0036] In response to the target accuracy being no greater than a preset accuracy threshold, controlling the robot to move according to a mission navigation map and target environment data collected by at least one sensor;

[0037] In response to the target accuracy being greater than the preset accuracy threshold, the robot is controlled to move according to target environment data collected by at least one sensor.

[0038] In one embodiment, the motion control module may include:

[0039] a data acquisition unit, configured to acquire target environment data collected by a target sensor combination corresponding to the target motion pattern, wherein different motion patterns correspond to different sensor combinations, different sensor combinations have different accuracy, and the accuracy of the motion pattern is positively correlated with the accuracy of the sensor combination;

[0040] A motion control unit is used to control the robot to move according to the target environment data.

[0041] In one embodiment, the data acquisition unit is specifically configured to:

[0042] Obtaining environmental data collected by each sensor in the target sensor combination corresponding to the target motion pattern;

[0043] Each environmental data is fused based on the preset weight of each sensor to obtain target environmental data.

[0044] In one embodiment, the data acquisition unit is specifically configured to:

[0045] Performing coordinate transformation on at least one environmental data to unify the coordinate system of each environmental data;

[0046] Each environmental data is fused based on the preset weight of each sensor to obtain target environmental data.

[0047] In one embodiment, the motion control module is specifically configured to:

[0048] Determining a target motion speed of the robot according to the target motion mode, wherein different motion modes correspond to different motion speeds, and the accuracy of the motion mode is negatively correlated with the motion speed;

[0049] The robot is controlled to move based on the target movement speed.

[0050] In one embodiment, the motion control module is specifically configured to:

[0051] Determining a target distance threshold according to a target motion mode, wherein different motion modes correspond to different distance thresholds, and the accuracy of the motion mode is negatively correlated with the distance threshold;

[0052] In response to the distance between the robot and the target position of the current task phase being less than the target distance threshold, the robot is controlled to stop moving.

[0053] In one embodiment, in response to the current task stage being the last task stage in the navigation task, the motion control device further comprises:

[0054] The posture determination module is used to determine the target position of the navigation task based on the target environment data collected by at least one sensor; and determine the target position and target posture of the current task stage based on the target position of the navigation task and the task content of the navigation task.

[0055] In a third aspect, the present application provides a computer program product, comprising a computer program / instruction, which implements the steps of the method described in any embodiment when executed by a processor.

[0056] In a fourth aspect, the present application provides a robot comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in any one of the above embodiments when executing the program.

[0057] In a fifth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0058] The technical solutions provided by the embodiments of the present disclosure may have the following beneficial effects:

[0059] In the embodiment of the present disclosure, the navigation task performed by the robot is divided into multiple task stages, each task stage corresponds to a motion mode of different precision, and the target motion mode corresponding to the current task stage is determined according to the current task stage that the robot is performing. Furthermore, in the task stage with low precision requirements, the motion mode corresponding to the low precision is used to control the robot to move, which can strictly control the cost and maximize the efficiency of the robot in performing the navigation task; in the task stage with high precision requirements, the motion mode corresponding to the high precision is used to control the robot to move, which can meet the precision requirements of the current task stage and perform the navigation task more accurately, solving the problem in the related technology that it is impossible to take into account both high precision and high efficiency when the robot performs the navigation task, and achieving the effect of improving the adaptability of the robot in facing navigation tasks with different precision requirements.

[0060] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0062] Figure 1 The figure is a flow chart of a motion control method shown in some exemplary embodiments.

[0063] Figure 2is a flow chart of another motion control method shown in some exemplary embodiments.

[0064] Figure 3 is a flow chart of yet another motion control method shown in some exemplary embodiments.

[0065] Figure 4 is a flow chart of yet another motion control method shown in some exemplary embodiments.

[0066] Figure 5 is a flow chart of yet another motion control method shown in some exemplary embodiments.

[0067] Figure 6 is a block diagram of a motion control device showing some exemplary embodiments.

[0068] Figure 7 is a structural diagram of a robot showing some exemplary embodiments. DETAILED DESCRIPTION

[0069] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0070] The terms used in this disclosure are for the purpose of describing specific embodiments only and are not intended to limit the 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.

[0071] It should be understood that although the terms first, second, third, etc. may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this disclosure, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining."

[0072] With the increasing popularity and application of robotics technology, robots have become an integral part of human society, driving innovation and development in industries such as industry, services, and healthcare. With the continuous advancement and innovation of technology, robots will continue to play an important role and bring more convenience and well-being to humanity.

[0073] In related technologies, robots often experience low accuracy or low efficiency when performing navigation tasks. In one case, improving navigation efficiency reduces accuracy, resulting in poor performance. In another case, improving accuracy reduces efficiency, resulting in longer navigation times.

[0074] In order to solve the above problems, the present disclosure proposes a motion control method, which is applied to the scenario where the robot performs a navigation task. Optionally, the motion control method can be performed by a motion control system that controls the motion of the robot. Optionally, the motion control system can be integrated into the robot locally or in a cloud server. Optionally, the robot can determine the current task stage of the robot by interacting with the motion control system integrated in the cloud server, or directly through the motion control system integrated locally, during the robot's execution of the navigation task, and then determine the target motion mode of different precisions corresponding to the current task stage based on the current task stage, and then control the robot to move based on the target motion mode. Alternatively, the motion control system can be integrated both locally in the robot and in the cloud server. When the computing demand is low, it can be processed directly by the motion control system integrated in the robot locally; when the computing demand is high, it can be processed by the motion control system integrated in the cloud server by interacting with the motion control system integrated in the cloud server.

[0075] The first aspect of the present disclosure provides a motion control method. Figure 1 , which includes steps 101 to 103:

[0076] S101, during the process of a robot performing a navigation task, determining a current task phase of the robot.

[0077] The navigation task refers to the task the robot is currently performing, for example, starting from the current position A and moving forward to shake hands with the task target C. This method can pre-divide the navigation task into multiple task stages with different accuracy requirements based on the task content. The current task stage refers to the task stage the robot is currently performing, for example, it can be the first task stage in the navigation task described above, that is, moving 5 meters from the current position A to the target position B of the current task stage. It should be noted that the target position of the navigation task is not the same as the target position of the multiple task stages within the navigation task.

[0078] Optionally, during the process of the robot performing a navigation task, the robot may interact with at least one sensor on the robot to obtain environmental data collected by the sensor, determine the robot's current position based on the obtained environmental data, determine the portion of the robot's execution based on the robot's current position and the initial position of the navigation task, and then determine the robot's current task stage based on the percentage of the robot's execution of the task in the entire navigation task. For example, if the navigation task is divided into three task stages, with the first stage being 0% to 50%, the second stage being 50% to 80%, and the third stage being 80% to 100%, and based on the robot's current position and the initial position of the navigation task, it is determined that the percentage of the robot's execution of the task in the entire navigation task is 30%, then the robot's current task stage can be determined to be the first stage of the navigation task.

[0079] S102: Determine a target motion mode according to the current task stage.

[0080] The navigation task includes multiple task phases, each of which corresponds to a different motion mode, and there are differences in accuracy between different motion modes. For example, if the navigation task includes three task phases, the motion mode corresponding to the first phase can be a low-precision motion mode, the motion mode corresponding to the second phase can be a medium-precision motion mode, and the motion mode corresponding to the third phase can be a high-precision motion mode. The target motion mode refers to the motion mode of the robot performing the current task phase, and can include target motion parameters, target sensor combinations, etc.

[0081] Optionally, after determining the current task stage of the robot, the target motion mode corresponding to the current task stage may be determined based on a predetermined correspondence between the task stage and the motion mode.

[0082] S103: Control the robot to move according to the target motion mode.

[0083] Optionally, after determining the target motion mode of the robot, the target motion mode can be used to control the robot's movement. For example, a target sensor combination in the target motion mode can be used to collect environmental data around the robot, and the robot can be controlled to move based on the target motion parameters in the target motion mode to perform the current task phase.

[0084] It should be noted that when a change is detected in the current task stage of the robot, it is necessary to redetermine the target motion mode corresponding to the changed task stage according to the changed task stage, and control the robot to move based on the redetermined target motion mode.

[0085] In the embodiment of the present disclosure, the navigation task performed by the robot is divided into multiple task stages, each task stage corresponds to a motion mode of different precision, and the target motion mode corresponding to the current task stage is determined according to the current task stage that the robot is performing. Furthermore, in the task stage with low precision requirements, the motion mode corresponding to the low precision is used to control the robot to move, which can strictly control the cost and maximize the efficiency of the robot in performing the navigation task; in the task stage with high precision requirements, the motion mode corresponding to the high precision is used to control the robot to move, which can meet the precision requirements of the current task stage and perform the navigation task more accurately, solving the problem in the related technology that it is impossible to take into account both high precision and high efficiency when the robot performs the navigation task, and achieving the effect of improving the adaptability of the robot in facing navigation tasks with different precision requirements.

[0086] In some embodiments of the present disclosure, different motion modes in the above embodiments can be divided according to differences in at least one dimension, such as path planning method, sensor combination, motion speed, distance threshold, etc. The differences in these dimensions are introduced in detail below.

[0087] In terms of path planning methods, the data used for path planning are different for motion modes with different precision.

[0088] Based on the difference in this dimension, when executing step S103, you can Figure 2 The steps shown are completed, specifically including steps 201 to 204:

[0089] S201: Determine a target accuracy of the target motion pattern according to the target motion pattern.

[0090] Among them, target accuracy refers to the accuracy corresponding to the target motion mode.

[0091] Optionally, after the target motion pattern is determined, a pre-set target accuracy may be extracted from the target motion pattern.

[0092] S202, determine whether the target accuracy is greater than a preset accuracy threshold; if not, execute S203; if so, execute S204.

[0093] The preset accuracy threshold refers to a pre-set accuracy threshold.

[0094] S203 : In response to the target accuracy being no greater than a preset accuracy threshold, controlling the robot to move according to the task navigation map and target environment data collected by at least one sensor.

[0095] The task navigation map refers to a pre-built, lower-precision map of the navigation task. This map can be constructed by pre-detecting the environment in which the navigation task is to be performed. The target environment data refers to environmental data collected by at least one sensor from the robot's surroundings.

[0096] Optionally, when the target accuracy is not greater than a preset accuracy threshold, an advanced path planning algorithm can be used based on a pre-built task navigation map and in combination with target environment data collected by at least one sensor to determine the target path of the current task stage, and based on the determined target path, the robot can be controlled to move to execute the current task stage.

[0097] S204 : In response to the target accuracy being greater than the preset accuracy threshold, controlling the robot to move according to target environment data collected by at least one sensor.

[0098] Optionally, when the target accuracy is greater than a preset accuracy threshold, the target environment data collected by the sensor can be obtained by interacting with at least one sensor, and then the target path of the current task stage can be planned, and based on the determined target path, the robot can be controlled to move to execute the current task stage.

[0099] It can be understood that by comparing the target accuracy of the target motion mode with the preset accuracy, when the target accuracy is not greater than the preset accuracy threshold, the task navigation map and target environment data can be used to determine the target path more quickly, thereby meeting the low-precision requirements of the current task stage and achieving the effect of controlling the robot to perform efficient movement; and when the target accuracy is greater than the preset accuracy threshold, the target path can be determined more accurately based on the target environment data collected by at least one sensor, thereby meeting the high-precision requirements of the current task stage and achieving the effect of controlling the robot to perform high-precision movement.

[0100] In terms of sensor combination, the sensor combination used to collect environmental data is different for motion modes with different precision.

[0101] Based on the difference in this dimension, in step S103, Figure 3 The steps shown are completed, specifically including step 301 to step 302:

[0102] S301: Acquire target environment data collected by a target sensor combination corresponding to the target motion mode.

[0103] Different motion modes correspond to different sensor combinations, and there are differences in accuracy between different sensor combinations. The accuracy of the motion mode is positively correlated with the accuracy of the sensor combination. That is, the higher the accuracy of the motion mode, the higher the accuracy of the corresponding sensor combination; conversely, the lower the accuracy of the motion mode, the lower the accuracy of the corresponding sensor combination. For example, if the motion mode is a low-precision motion mode, the corresponding sensor combination is a low-precision sensor combination; if the motion mode is a high-precision motion mode, the corresponding sensor combination is a high-precision sensor combination.

[0104] Optionally, after determining the target motion mode corresponding to the current task stage, the target sensor combination can be determined based on the target motion mode, and then the target sensor combination can be controlled to collect the target environment data around the robot, and the collected target environment data can be obtained by interacting with the target sensor combination.

[0105] S302: Control the robot to move according to the target environment data.

[0106] Optionally, after obtaining the target environment data collected by the target sensor combination, a pre-set path planning algorithm can be used according to the target environment data to determine the target path of the current task stage; and then the robot can be controlled to move based on the target path.

[0107] It can be understood that by determining the target sensor combination based on the target motion mode, and then obtaining the target environment data collected by the target sensor combination, and controlling the robot to move according to the target environment data, the cost of the robot performing the current task stage can be reduced while the obtained target environment data meets the accuracy requirements.

[0108] Based on the above embodiments, in an exemplary embodiment, an implementable method is provided for the above S301, which can obtain the environmental data collected by each sensor in the target sensor combination corresponding to the target motion mode; and fuse each environmental data based on the preset weight of each sensor to obtain the target environmental data.

[0109] Optionally, after determining the target sensor combination corresponding to the target motion mode, the environmental data collected by each sensor in the target sensor combination can be obtained; further, the preset weight of each sensor in the pre-set target sensor combination can be obtained, and the environmental data collected by each sensor can be fused according to the preset weight of each sensor to obtain the target environmental data. For example, if the target sensor combination includes three sensors: a low-precision camera, a lidar, and a GPS sensor, and the preset weight of the low-precision camera is 0.15, the preset weight of the lidar is 0.45, and the preset weight of the GPS sensor is 0.4, then the environmental data collected by the three sensors can be fused according to the preset weights of the three sensors to obtain the target environmental data.

[0110] It can be understood that after obtaining the environmental data collected by each sensor in the target sensor combination, by introducing the preset weight of each sensor and fusing each environmental data according to the preset weight of each sensor, the target environmental data can be obtained more accurately, and then the robot can be controlled more accurately to perform navigation tasks.

[0111] Furthermore, after obtaining the environmental data collected by each sensor in the target sensor combination, the coordinates of at least one environmental data can be transformed to unify the coordinate system of each environmental data; each environmental data is fused based on the preset weight of each sensor to obtain the target environmental data.

[0112] Optionally, a target coordinate system can be set in advance, or the coordinate system of the data collected by a sensor in the target sensor combination can be used as the target coordinate system. After obtaining the environmental data collected by each sensor in the target sensor combination, the environmental data whose coordinate system is different from the target coordinate system is input into a pre-set coordinate conversion model. Through the coordinate conversion model, each environmental data is converted into environmental data under the target coordinate system, so that the coordinates of the environmental data collected by each sensor in the target sensor combination are unified; and then based on the preset weight of each sensor and according to each environmental data, the target environmental data can be obtained more accurately, thereby achieving the effect of improving the accuracy of the robot in performing navigation tasks.

[0113] In terms of movement speed, for movement modes with different precision, the movement speed of controlling the robot to complete the current task stage is different.

[0114] Based on the difference in this dimension, an implementable method is provided for the above S103, which can determine the target movement speed of the robot according to the target movement mode; and control the robot to move based on the target movement speed.

[0115] Different motion modes correspond to different motion speeds, and the precision of the motion mode is negatively correlated with the motion speed. That is, the higher the precision of the motion mode, the lower the motion speed; conversely, the lower the precision of the motion mode, the higher the motion speed. The target motion speed refers to the speed at which the robot is performing the current task. For example, if the target motion mode is a low-precision motion mode, the target motion speed can be high; if the target motion mode is a high-precision motion mode, the target motion speed can be low.

[0116] Optionally, after determining the target motion mode of the robot, the target motion speed can be determined according to the target motion mode based on the correspondence between the preset motion mode and the motion speed; and then, the robot is controlled to move based on the determined target motion speed.

[0117] It can be understood that by setting different movement speeds for different movement modes, determining the target movement speed according to the target movement mode, and then controlling the robot to move based on the target movement speed, it is possible to more efficiently control the robot to perform navigation tasks while meeting the accuracy requirements of the current task stage.

[0118] In terms of distance threshold, different precision motion modes have different distance thresholds for determining whether the robot has completed the current task stage.

[0119] Based on the difference in this dimension, in step S103, Figure 4 The steps shown are completed, specifically including step 401 to step 402:

[0120] S401: Determine a target distance threshold according to a target motion pattern.

[0121] Different motion modes correspond to different distance thresholds. The accuracy of the motion mode is negatively correlated with the distance threshold: lower accuracy corresponds to a larger distance threshold, and vice versa. The target distance threshold is the pre-set distance threshold between the robot's current position and the target position for the current mission phase.

[0122] Optionally, after determining the target motion mode, a target distance threshold may be determined based on a predetermined correspondence between the motion mode and the distance threshold. For example, if the target motion mode is a low-precision motion mode, the target distance threshold may be determined to be 0.5 meters; if the target motion mode is a high-precision motion mode, the target distance threshold may be determined to be 0.1 meters.

[0123] S402 : In response to the distance between the robot and the target position of the current task phase being less than the target distance threshold, controlling the robot to stop moving.

[0124] The target position of the current mission stage can be determined by the mission percentage represented by the current mission stage in the navigation task. For example, if the mission percentage represented by the current mission stage in the navigation task is between 0% and 50%, and the total distance of the navigation task is 50 meters, the position corresponding to 50% of the navigation task, that is, the position at the 25th meter in the navigation task, can be used as the target position of the current mission stage.

[0125] Optionally, the current position of the robot can be determined through environmental data collected by at least one sensor, and then the distance between the robot and the target position of the current task stage can be determined; further, the determined distance is compared with the target distance threshold. If it is determined that the distance is less than the target distance threshold, the robot can be controlled to stop moving to end the execution of the current task stage.

[0126] It can be understood that by setting different distance thresholds for different motion modes and determining the target distance threshold according to the target motion mode, when the distance between the robot and the target position of the current task stage is less than the target distance threshold, the robot is judged to have completed the current task stage and the robot is controlled to stop moving, which can more accurately meet the different precision requirements of each task stage and thus more flexibly control the robot to perform navigation tasks.

[0127] It should be noted that when the current task stage is not the last task stage in the navigation task, after controlling the robot to stop moving to end the execution of the current task stage, the current task stage can be switched to the next task stage, and the corresponding motion mode can be re-determined according to the next task stage, so that the robot can adaptively adjust the motion modes corresponding to different task stages when performing the navigation task.

[0128] Based on the above embodiment, in an optional embodiment, in response to the current task stage being the last task stage in the navigation task, the following steps may be performed: Figure 5 The steps shown are used to determine the target position and target posture of the robot, specifically including steps 501 to 502:

[0129] S501: Determine a target location of the navigation task based on target environment data collected by at least one sensor.

[0130] The target position of the navigation task refers to the location of the task target of the navigation task performed by the robot. For example, if the navigation task is to start from the initial position A and shake hands with the task target C, the target position of the navigation task can be position D where the task target C is located.

[0131] Optionally, when determining that the current mission stage is the last mission stage of the navigation mission, the environmental data collected by the at least one sensor can be obtained by interacting with the at least one sensor, and then the target position of the navigation mission can be determined based on the collected environmental data.

[0132] S502: Determine the target position and target posture of the current task phase according to the target position of the navigation task and the task content of the navigation task.

[0133] The target position of the current mission phase refers to the position that the robot needs to reach during the current mission phase, and the target posture refers to the posture that the robot needs to assume during the current mission phase. The task content of the navigation task refers to the specific content of the task that the robot needs to perform.

[0134] Optionally, after determining the target location of the navigation task, the target location and target posture for the current task phase can be determined based on the task content and the target location of the navigation task, using a pre-defined posture determination model. For example, if the target location of the navigation task is location D and the task content is to shake hands with task target C, the target location E for the current task phase can be location E on the target path, 0.5 meters away from task target C, and the target posture can be facing task target C and posing for a handshake.

[0135] It can be understood that by combining the target position of the navigation task with the task content of the navigation task, the target position and target posture of the current task stage can be determined more reasonably, and the effect of more accurately controlling the robot to perform the navigation task can be achieved.

[0136] The second aspect of the present disclosure provides a motion control device. Figure 6 , the above-mentioned motion control device includes:

[0137] The stage determination module 601 is used to determine the current task stage of the robot during the robot's execution of the navigation task;

[0138] A mode determination module 602 is configured to determine a target motion mode according to the current mission stage, wherein the navigation mission includes multiple mission stages, each mission stage corresponds to a different motion mode, and different motion modes have different accuracy;

[0139] The motion control module 603 is used to control the robot to move according to the target motion mode.

[0140] In one embodiment, the motion control module is specifically configured to:

[0141] determining a target accuracy of the target motion pattern according to the target motion pattern;

[0142] In response to the target accuracy being no greater than a preset accuracy threshold, controlling the robot to move according to a mission navigation map and target environment data collected by at least one sensor;

[0143] In response to the target accuracy being greater than the preset accuracy threshold, the robot is controlled to move according to target environment data collected by at least one sensor.

[0144] In one embodiment, the motion control module may include:

[0145] a data acquisition unit, configured to acquire target environment data collected by a target sensor combination corresponding to the target motion pattern, wherein different motion patterns correspond to different sensor combinations, different sensor combinations have different accuracy, and the accuracy of the motion pattern is positively correlated with the accuracy of the sensor combination;

[0146] A motion control unit is used to control the robot to move according to the target environment data.

[0147] In one embodiment, the data acquisition unit is specifically configured to:

[0148] Obtaining environmental data collected by each sensor in the target sensor combination corresponding to the target motion pattern;

[0149] Each environmental data is fused based on the preset weight of each sensor to obtain target environmental data.

[0150] In one embodiment, the data acquisition unit is specifically configured to:

[0151] Performing coordinate transformation on at least one environmental data to unify the coordinate system of each environmental data;

[0152] Each environmental data is fused based on the preset weight of each sensor to obtain target environmental data.

[0153] In one embodiment, the motion control module is specifically configured to:

[0154] Determining a target motion speed of the robot according to the target motion mode, wherein different motion modes correspond to different motion speeds, and the accuracy of the motion mode is negatively correlated with the motion speed;

[0155] The robot is controlled to move based on the target movement speed.

[0156] In one embodiment, the motion control module is specifically configured to:

[0157] Determining a target distance threshold according to a target motion mode, wherein different motion modes correspond to different distance thresholds, and the accuracy of the motion mode is negatively correlated with the distance threshold;

[0158] In response to the distance between the robot and the target position of the current task phase being less than the target distance threshold, the robot is controlled to stop moving.

[0159] In one embodiment, in response to the current task stage being the last task stage in the navigation task, the motion control device further comprises:

[0160] The posture determination module is used to determine the target position of the navigation task based on the target environment data collected by at least one sensor; and determine the target position and target posture of the current task stage based on the target position of the navigation task and the task content of the navigation task.

[0161] The implementation process of the functions and effects of each module in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0162] A third aspect of the present disclosure provides a computer program product, comprising a computer program / instruction, which implements the method described in the first aspect when executed by a processor.

[0163] For the device embodiments and computer program product embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the partial description of the method embodiments. In addition, the device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the disclosed solution. Those of ordinary skill in the art can understand and implement it without paying any creative work.

[0164] In a fourth aspect, some embodiments of the present disclosure provide an electronic device, which may be a robot or other device equipped with a motion control system. For example, see Figure 7 , which shows the structure of the robot, the robot includes a memory and a processor, the memory is used to store computer instructions that can be run on the processor, and the processor is used to perform motion control based on the method described in any one of the first aspects when executing the computer instructions.

[0165] In a fifth aspect, the present disclosure, in exemplary embodiments, further provides a non-transitory computer-readable storage medium including instructions, such as a memory including instructions, wherein the instructions can be executed by a processor of a robot or a computer device to implement the aforementioned robot motion control method. For example, the non-transitory computer-readable storage medium can be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

[0166] The foregoing description describes specific embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0167] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the inventions claimed herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not claimed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0168] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

[0169] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A motion control method, characterized in that: The method comprises: During the process of the robot performing the navigation task, determining the current task phase of the robot; Determining a target motion mode according to the current mission stage, wherein the navigation mission includes multiple mission stages, each mission stage corresponds to a different motion mode, and there are differences in accuracy between different motion modes; The robot is controlled to move according to the target motion pattern.

2. The method according to claim 1, characterized in that The step of controlling the robot to move according to the target motion mode includes: determining a target accuracy of the target motion pattern according to the target motion pattern; In response to the target accuracy being no greater than a preset accuracy threshold, controlling the robot to move according to a mission navigation map and target environment data collected by at least one sensor; In response to the target accuracy being greater than the preset accuracy threshold, the robot is controlled to move according to target environment data collected by at least one sensor.

3. The method according to claim 1, characterized in that The step of controlling the robot to move according to the target motion mode includes: Acquire target environment data collected by a target sensor combination corresponding to the target motion mode, wherein different motion modes correspond to different sensor combinations, different sensor combinations have different accuracy, and the accuracy of the motion mode is positively correlated with the accuracy of the sensor combination; The robot is controlled to move according to the target environment data.

4. The method according to claim 3, characterized in that The acquiring target environment data collected by the target sensor combination corresponding to the target motion mode includes: Obtaining environmental data collected by each sensor in the target sensor combination corresponding to the target motion pattern; Each environmental data is fused based on the preset weight of each sensor to obtain target environmental data.

5. The method according to claim 4, characterized in that The fusing of each environmental data based on the preset weight of each sensor to obtain target environmental data includes: Performing coordinate transformation on at least one environmental data to unify the coordinate system of each environmental data; Each environmental data is fused based on the preset weight of each sensor to obtain target environmental data.

6. The method according to claim 1, wherein The step of controlling the robot to move according to the target motion mode includes: Determining a target motion speed of the robot according to the target motion mode, wherein different motion modes correspond to different motion speeds, and the accuracy of the motion mode is negatively correlated with the motion speed; The robot is controlled to move based on the target movement speed.

7. The method according to claim 1, characterized in that The step of controlling the robot to move according to the target motion mode includes: Determining a target distance threshold according to a target motion mode, wherein different motion modes correspond to different distance thresholds, and the accuracy of the motion mode is negatively correlated with the distance threshold; In response to the distance between the robot and the target position of the current task phase being less than the target distance threshold, the robot is controlled to stop moving.

8. The method according to claim 7, characterized in that In response to the current task stage being the last task stage in the navigation task, the method further includes: determining a target location of the navigation task based on target environment data collected by at least one sensor; The target position and target posture of the current task phase are determined according to the target position of the navigation task and the task content of the navigation task.

9. A motion control device, characterized in that: The device comprises: a stage determination module, configured to determine a current task stage of the robot during the robot's execution of a navigation task; a mode determination module, configured to determine a target motion mode according to the current mission stage, wherein the navigation mission includes multiple mission stages, each mission stage corresponds to a different motion mode, and there are differences in accuracy between different motion modes; A motion control module is used to control the robot to move according to the target motion mode.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 8 is implemented.

11. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 8 is implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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