Autonomous mobile device and control method thereof

Abstract

The invention provides a control method of an autonomous mobile device. The method comprises the steps of obtaining a posture of a target point; determining a motion control parameter based on the attitude of the target point; and controlling the autonomous mobile device to move along the motion track according to the motion control parameter. The curvature function of the motion trajectory includes an inverse proportional function of the distance between the autonomous mobile device and the target point, the coefficients of this inverse proportional function including terms functionally related to a lateral offset between the autonomous mobile device and the target point, and the lateral offset is related to the orientation of the target point. The invention further provides an autonomous moving device.

Description

Technical Field

[0001] The present disclosure relates to the field of automatic control technology, and more particularly to an autonomous mobile device and a control method thereof during stages such as alignment. Background Art

[0002] Autonomous mobile units play a key role in many fields, such as automated manufacturing, robotic navigation, precision medical devices, and unmanned transportation systems. However, there are still many problems to be solved in the alignment (also known as docking) control of current autonomous mobile units.

[0003] One of the problems comes from the algorithms. Specifically, the motion control systems of general autonomous mobile units use relatively basic path planning algorithms, which may not fully consider the environment and operation requirements during the alignment stage. Therefore, when these path planning algorithms are applied to the alignment stage, it may lead to unnecessary adjustments and corrections, affecting the smoothness and efficiency of the alignment process.

[0004] Another problem comes from the stability of the sensors. During fine adjustments and precise alignment, the stability of the sensors is particularly important. If the data of the sensors fluctuates or drifts too violently, it will not only affect the smoothness and accuracy during alignment, but also may affect the reliability and safety of the overall system. Therefore, it is necessary to propose a method to control the autonomous mobile unit to enable smoother and more precise alignment operations. Summary of the Invention

[0005] In view of this, the present disclosure provides a control method for an autonomous mobile device, which can correct the lateral offset between itself and the target point faster, and improve the alignment smoothness and efficiency between the autonomous mobile device and the target point.

[0006] A first aspect of the present disclosure proposes a control method for an autonomous mobile device, including: obtaining the attitude of a target point; determining motion control parameters based on the attitude of the target point; and controlling the autonomous mobile device to move along a motion trajectory according to the motion control parameters. The path curvature of the motion trajectory includes an inverse proportional function of the distance between the autonomous mobile device and the target point, and the coefficient of the inverse proportional function includes a term related to the lateral offset between the autonomous mobile device and the target point, where the lateral offset is related to the orientation of the target point.

[0007] In some embodiments of the first aspect, the lateral offset is also related to the position of the autonomous mobile device.

[0008] In some embodiments of the first aspect, obtaining the pose of the target point includes: obtaining multiple target poses of the target point at multiple time points through a sensor system; calculating a weighted average of the multiple target poses to obtain the current target pose; and calculating the current relative pose between the target point and the autonomous mobile device based on the current target pose.

[0009] In some embodiments of the first aspect, obtaining multiple target poses of the target point at multiple time points through a sensor system includes: detecting the target point through the sensor system to obtain a sensing result; and converting the sensing result into the odometry coordinate system to obtain one of the target poses.

[0010] In some embodiments of the first aspect, the method further includes: detecting the movement of the autonomous mobile device through the sensor system; calculating the current device pose of the autonomous mobile device in the odometry coordinate system based on the movement; and calculating the current relative pose between the target point and the autonomous mobile device based on the current target pose and the current device pose.

[0011] In some embodiments of the first aspect, the multiple target poses at multiple time points include a first target pose at a first time point, which is detected and obtained by a camera on the autonomous mobile device, and the weight corresponding to the first target pose is negatively correlated with the speed of the autonomous mobile device at the first time point.

[0012] In some embodiments of the first aspect, the multiple target poses at multiple time points include a first target pose at a first time point, which is detected and obtained by a lidar on the autonomous mobile device, and the weight corresponding to the first target pose is negatively correlated with the distance between the target point and the autonomous mobile device.

[0013] In some embodiments of the first aspect, the method further includes: judging the pose difference between the autonomous mobile device and the target point; deciding whether to stop the autonomous mobile device based on the pose difference; after stopping the autonomous mobile device, reacquiring the pose of the target point through the sensor system; and correcting the pose error of the autonomous mobile device based on the reacquired pose of the target point. The pose error includes at least one of a lateral error, a longitudinal error, and an angular error.

[0014] In some embodiments of the first aspect, the motion control parameters include a linear velocity and an angular velocity. Determining the motion control parameters based on the pose of the target point includes: determining the linear velocity; calculating the current curvature based on the current distance between the autonomous mobile device and the target point, the current orientation of the autonomous mobile device, and the current orientation of the target point; and calculating the angular velocity based on the linear velocity and the current curvature.

[0015] In some embodiments of the first aspect, the autonomous mobile device includes a Non-Omnidirectional Drive system.

[0016] A second aspect of the present disclosure presents an autonomous mobile device, including a drive system and a controller coupled to the drive system. The controller is configured to obtain the pose of a target point; determine motion control parameters based on the pose of the target point; and control the autonomous mobile device to move along a motion trajectory according to the motion control parameters. The path curvature of the motion trajectory includes an inverse proportional function of the distance between the autonomous mobile device and the target point, and the coefficient of the inverse proportional function includes a term related to the lateral offset between the function and the autonomous mobile device and the target point, where the lateral offset is related to the orientation of the target point.

[0017] In some embodiments of the second aspect, the lateral offset is further related to the position of the autonomous mobile device.

[0018] In some embodiments of the second aspect, obtaining the pose of the target point includes: obtaining multiple target poses of the target point at multiple time points through a sensor system; calculating a weighted average of the multiple target poses to obtain a current target pose; and calculating a current relative pose between the target point and the autonomous mobile device based on the current target pose.

[0019] In some embodiments of the second aspect, obtaining multiple target poses of the target point at multiple time points through a sensor system includes: detecting the target point through a sensor system to obtain a sensing result; and converting the sensing result into an odometry coordinate system to obtain one of the target poses.

[0020] In some embodiments of the second aspect, the controller is further configured to: detect the motion of the autonomous mobile device through a sensor system; calculate a current device pose of the autonomous mobile device in the odometry coordinate system based on the motion; and calculate a current relative pose between the target point and the autonomous mobile device based on the current target pose and the current device pose.

[0021] In some embodiments of the second aspect, the multiple target poses at multiple time points include a first target pose at a first time point, which is detected and obtained by a camera on the autonomous mobile device, and the weight corresponding to the first target pose is negatively correlated with the speed of the autonomous mobile device at the first time point.

[0022] In some embodiments of the second aspect, the multiple target poses at multiple time points include a first target pose at a first time point, which is detected and obtained by a lidar on the autonomous mobile device, and the weight corresponding to the first target pose is negatively correlated with the distance between the target point and the autonomous mobile device.

[0023] In some embodiments of the second aspect, the method further includes: determining an attitude difference between the autonomous mobile device and the target point; determining whether to stop the autonomous mobile device based on the attitude difference; after stopping the autonomous mobile device, reacquiring the attitude of the target point through the sensor system; and correcting the attitude error of the autonomous mobile device based on the reacquired attitude of the target point. The attitude error includes at least one of a lateral error, a longitudinal error, and an angular error.

[0024] In some embodiments of the second aspect, the motion control parameters include a linear velocity and an angular velocity. Determining the motion control parameters based on the attitude of the target point includes: determining the linear velocity; calculating a current curvature based on the current distance between the autonomous mobile device and the target point, the current orientation of the autonomous mobile device, and the current orientation of the target point; and calculating the angular velocity based on the linear velocity and the current curvature.

[0025] In some embodiments of the second aspect, the drive system includes a non-omnidirectional drive system.

[0026] Based on the above, the autonomous mobile device and its control method proposed by the embodiments of the present disclosure can correct the lateral offset between itself and the target point faster through adjusting the algorithm used in path calculation, improving the alignment fluency and efficiency between the autonomous mobile device and the target point. In addition, by performing coordinate transformation and averaging on the data acquired by the sensor system at multiple time points, the problems caused by insufficient stability of the sensor system can be effectively solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings exemplarily illustrate embodiments and constitute a part of the specification, and are used together with the written description of the specification to explain the exemplary embodiments. Obviously, the drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In all the drawings, the same reference numerals refer to similar but not necessarily identical elements.

[0028] Figure 1 Schematic block diagram of an autonomous mobile device according to an embodiment of the present disclosure;

[0029] Figure 2 Schematic diagram of a task phase according to an embodiment of the present disclosure;

[0030] Figure 3 Schematic diagram of a control method according to an embodiment of the present disclosure;

[0031] Figure 4 Flowchart of a control method according to an embodiment of the present disclosure;

[0032] Figure 5Flowchart for obtaining the attitude of the target point according to an embodiment of the present disclosure;

[0033] Figure 6 Flowchart for attitude error correction according to an embodiment of the present disclosure;

[0034] Figures 7A to 7C Schematic diagram for attitude error correction according to an embodiment of the present disclosure. Detailed implementation manners

[0035] The following description contains specific information related to the exemplary embodiments in the present disclosure. The accompanying drawings and their detailed descriptions in the present disclosure are only exemplary embodiments. However, the present disclosure is not limited to these exemplary embodiments. Those skilled in the art will think of other variations and embodiments of the present disclosure. Unless otherwise specified, the same or corresponding elements in the drawings may be indicated by the same or corresponding reference numerals. In addition, the drawings and illustrations in the present disclosure are generally not drawn to scale and are not intended to correspond to actual relative sizes.

[0036] For the purpose of consistency and ease of understanding, the same features are labeled by reference numerals in the exemplary drawings (although this may not be the case in some examples). However, the features in different embodiments may be different in other aspects, and thus should not be narrowly limited to the features shown in the drawings.

[0037] For terms such as "at least one embodiment", "an embodiment", "multiple embodiments", "different embodiments", "some embodiments", "this embodiment", etc., it may indicate that the embodiments of the present disclosure so described may include specific features, structures, or characteristics, but not every possible embodiment of the present disclosure must include the specific features, structures, or characteristics. In addition, the repeated use of the phrase "in an embodiment", "in this embodiment" does not necessarily refer to the same embodiment, although they may be the same. In addition, phrases such as "embodiment" used in association with "the present disclosure" do not mean that all embodiments of the present disclosure must include specific features, structures, or characteristics, and it should be understood that "at least some embodiments of the present disclosure" include the described specific features, structures, or characteristics. The term "coupled" is defined as connected, whether directly or indirectly through an intermediate element, and is not necessarily limited to a physical connection. When the term "comprising" is used, it means "comprising but not limited to", which clearly indicates an open inclusion or relationship of the described combinations, groups, series, and equivalents.

[0038] In addition, for purposes of explanation and not limitation, specific details such as functional entities, technologies, agreements, standards, etc. are set forth to provide an understanding of the described technology. In other examples, detailed descriptions of well-known methods, technologies, systems, architectures, etc. are omitted to avoid obscuring the description with unnecessary details.

[0039] The terms "first", "second", "third", etc. in the specification of the present disclosure and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the term "comprising" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not limited to the listed steps or modules, but optionally further includes steps or modules not listed, or optionally further includes other steps or modules inherent to these processes, methods, products, or devices.

[0040] The embodiments of the present disclosure will be described below in conjunction with the accompanying drawings.

[0041] The embodiments of the present disclosure will take the movement in a two-dimensional plane as an example to illustrate the control method of the autonomous mobile device. However, the present disclosure does not limit the movement dimension applicable to the control method, and those skilled in the art can apply it to the movement of autonomous mobile devices in a three-dimensional space based on the disclosure content of the embodiments of the present disclosure.

[0042] Figure 1 The schematic block diagram of an autonomous mobile device according to an embodiment of the present disclosure is shown.

[0043] Please refer to Figure 1 , the autonomous mobile device 100 includes a drive system 110, a controller 120, and a sensor system 130, wherein both the drive system 110 and the sensor system 130 are coupled to the controller 120. Specifically, the autonomous mobile device 100 is a device capable of autonomously moving in an environment, such as unmanned aerial vehicles (UAVs), autonomous guided vehicles (AGVs), autonomous guided forklifts (AGFs), autonomous mobile robots (AMRs), etc., but the present disclosure is not limited thereto.

[0044] The drive system 110 is a system used to drive the autonomous mobile device 100 to move, and includes, for example, mechanical structures such as motors, wheels, or tracks.

[0045] In some embodiments, the drive system 110 includes a Non-Omnidirectional Drive system. Specifically, different from omnidirectional drive systems such as the Mecanum Wheel Drive system, the non-omnidirectional drive system can move linearly along a forward or backward path and change direction by steering rather than lateral movement. For example, the non-omnidirectional drive system includes a Differential Drive system, a Steered Wheel system, a Tracked Drive system, a Fixed-Axle Drive system, etc., but the present disclosure is not limited thereto.

[0046] In some embodiments, the drive system 110 of the autonomous mobile device 100 belongs to a differential drive system.

[0047] The controller 120 is used to control the overall operation of the autonomous mobile device 100, which includes, for example, a Central Processing Unit (CPU), or other programmable general-purpose or special-purpose microprocessors, digital signal processors (DSPs), programmable controllers, Application Specific Integrated Circuits (ASICs), Programmable Logic Devices (PLDs), or other similar components or combinations of these components, but the present disclosure is not limited thereto.

[0048] In some embodiments, the sensor system 130 includes a first sensor system and a second sensor system. Specifically, the first sensor system is used to sense the external environment of the autonomous mobile device 100, and the second sensor system is used to sense the movement of the autonomous mobile device 100.

[0049] For example, the first sensor system includes sensors such as lidar and cameras to detect the position and orientation of target points; the second sensor system includes sensors such as wheel speedometers and Inertial Measurement Units (IMUs) to detect the pose change of the autonomous mobile device 100. Change.

[0050] It is worth mentioning that, as used herein, "pose" includes position information (e.g., coordinates) and orientation information (e.g., pose angles).

[0051] Figure 2 Schematic diagram of a task phase according to an embodiment of the present disclosure.

[0052] Please refer to Figure 2 , in some embodiments, the tasks of the autonomous mobile device 100 include a navigation (Navigation) phase and a docking phase.

[0053] Specifically, the navigation phase is, for example, the phase in which the autonomous mobile device 100 moves from a starting point A to a location B; the docking phase is the phase in which the autonomous mobile device 100, after moving to the location B, more precisely docks to a target point T adjacent to the location B. For example, in the navigation phase, the autonomous mobile device 100 uses thresholds including a first distance threshold D th1 and other thresholds as the judgment criterion for whether it has reached the location B. In the docking phase, the autonomous mobile device 100 uses thresholds including a second distance threshold (not shown in Figure 2 ) and other thresholds as the judgment criterion for whether it has docked to the target point T. Since the docking phase requires higher precision, the second distance threshold is less than or equal to the first distance threshold D th1 .

[0054] In some embodiments, in addition to position information, the target point T also includes orientation information. For example, the starting point A can be the first workstation in a factory, the location B can be the second workstation in the factory, and the target point T can be a directional location in the second workstation for the autonomous mobile device 100 to park or dock.

[0055] It is worth mentioning that, in the following embodiments, the control of the autonomous mobile device 100 in the docking phase is used as an illustration of the control method proposed by the present disclosure. However, those skilled in the art should understand that the control method proposed by the present disclosure can also be applied to other task phases.

[0056] Figure 3 Schematic diagram of a control method according to an embodiment of the present disclosure; Figure 4 Flowchart of a control method according to an embodiment of the present disclosure. Figure 3 The parameters and reference numerals illustrated in

[0057] Please refer to Figure 3 and Figure 4, in operation 402, the controller 120 obtains the pose of the target point T. Specifically, the pose of the target point T includes at least one of the position information and the orientation information of the target point T.

[0058] In some embodiments, the controller 120 is coupled to a memory (not shown), and the memory is used to store an environmental map and the poses of at least one positioning point on the environmental map. When the target point T is one of the at least one positioning point, the controller 120 can obtain the pose of the target point T from the information in the memory, for example.

[0059] In some embodiments, the controller 120 obtains the pose of the target point T through the sensor system 130. Specifically, the sensor system 130 on the autonomous mobile device 100 can be used to detect the target point T to obtain the pose of the target point T relative to the autonomous mobile device 100.

[0060] In some embodiments, in order to avoid path unevenness caused by instability of the sensor system 130, the controller 120 performs arithmetic processing on the sensing results obtained by the sensor system 130 detecting the target point T, and then provides them for subsequent motion control.

[0061] Further, for the detailed operations of obtaining the pose of the target point T, please refer to Figure 5 , Figure 5 FIG. shows a flowchart of obtaining the pose of a target point according to an embodiment of the present disclosure.

[0062] In operation 502, the controller 120 obtains multiple target poses of the target point T at multiple time points through the sensor system 130.

[0063] Specifically, starting from the starting position (e.g., location B), the sensor system 130 detects the target point T at multiple time points to obtain multiple sensing results. These sensing results are presented in an egocentric coordinate system, for example, and the controller 120 converts these sensing results into the same absolute coordinate system to obtain multiple target poses.

[0064] For example, the sensor system 130 includes a camera with a first update rate (e.g., 60 Hz). At each time point (e.g., every 1 / 60 second), the sensor system 130 can obtain the pose of the target point T at each time point based on the environmental image captured by the camera. For example, the sensor system 130 includes a lidar with a second update rate (e.g., 20 Hz (usually between 10 - 30 Hz)). At each time point (e.g., every 1 / 20 second), the sensor system 130 can obtain the pose of the target point T at each time point based on the environmental image detected by the lidar.

[0065] For example, the controller 120 can transform the multiple sensing results obtained by the first sensor system into the same absolute coordinate system based on the self - pose change obtained by the second sensor system and the intrinsic parameters of the first sensor system.

[0066] In some embodiments, the controller 120, for example, determines an absolute coordinate system with the starting position as the origin, and transforms the poses of the target point T at multiple time points obtained through the sensor system 130 into this absolute coordinate system to obtain multiple target poses of the target point T at multiple time points. For example, the determined absolute coordinate system can be an odometer coordinate system.

[0067] In operation 504, the controller 120 calculates the weighted average of the multiple target poses to obtain the current target pose.

[0068] Specifically, the current target pose includes, for example, at least one of the current target position and the current target orientation. For example, the controller 120 calculates the weighted average of the multiple target positions of the target point T at multiple time points to obtain the current target position. For example, the controller 120 calculates the weighted average of the multiple target orientations of the target point T at multiple time points to obtain the current target orientation.

[0069] In some embodiments, the weights of the weighted average are all the same (e.g., 1).

[0070] In some embodiments, the weights used to calculate the weighted average are related (e.g., positively correlated) to the data credibility of the corresponding target pose. For example, the data credibility of the camera is negatively correlated with the moving speed of the camera. For example, the data credibility of the lidar is negatively correlated with the distance between the lidar and the target point T.

[0071] In some embodiments, the weights for calculating the weighted average of the multiple target poses detected and obtained by the camera in the sensor system 130 are negatively correlated with the speed of the autonomous mobile device 100 during camera shooting. For example, the multiple target poses detected and obtained by the camera include the first target pose at the first time point and the second target pose at the second time point. If the speed of the autonomous mobile device 100 is higher at the first time point than at the second time point, the weight corresponding to the first target pose is less than the weight corresponding to the second target pose.

[0072] In some embodiments, the weights for calculating the weighted average of the multiple target poses detected and obtained by the lidar in the sensor system 130 are negatively correlated with the distance between the autonomous mobile device 100 and the target point T during lidar shooting. For example, the multiple target poses detected and obtained by the lidar include the first target pose at the first time point and the second target pose at the second time point. If the distance between the autonomous mobile device 100 and the target point T is greater at the first time point than at the second time point, the weight corresponding to the first target pose is less than the weight corresponding to the second target pose.

[0073] In some embodiments, the weighted-averaged current target pose is used for subsequent motion control. Advantageously, through the calculation of the weighted average, the instability of the detection result of the target point T by the sensor system 130 can be corrected.

[0074] In operation 506, the controller 120 calculates the current relative pose between the target point T and the autonomous mobile device 100 based on the current target pose.

[0075] Specifically, the current relative pose is, for example, a pose represented in the autonomous coordinate system. Since the current target pose is, for example, in the odometry coordinate system, the controller 120 converts the current target pose of the target point T back into the autonomous coordinate system for subsequent motion control.

[0076] In some embodiments, the starting pose of the controller 120 is the origin in the odometry coordinate system. Therefore, based on the motion of the autonomous mobile device 100 detected by the sensor system 130 from the starting pose to the current time point, the controller 120 can calculate the current device pose of the autonomous mobile device 100 in the odometry coordinate system at the current time point. After obtaining the information of the current device pose of the autonomous mobile device 100 and the current target pose of the target point T in the odometry coordinate system, the controller 120 can calculate the current relative pose between the target point T and the autonomous mobile device 100. In other words, the current relative pose can be the current pose of the target point T in the autonomous coordinate system of the autonomous mobile device 100.

[0077] Please go back to Figure 4, in operation 404, the controller 120 determines motion control parameters based on the attitude of the target point T; in operation 406, the controller 120 controls the autonomous mobile device 100 to move along the motion trajectory according to the motion control parameters.

[0078] Specifically, the controller 120 determines motion control parameters such that the path curvature of the motion trajectory includes an inverse proportional function of the distance r between the autonomous mobile device 100 and the target point T, and the coefficient of this inverse proportional function includes terms functionally related to the lateral offset e between the autonomous mobile device 100 and the target point T. The motion control parameters for controlling the drive system 110 of the autonomous mobile device 100 include, for example, linear velocity and angular velocity, but the present disclosure is not limited thereto. lat The motion control parameters for controlling the drive system 110 of the autonomous mobile device 100 include, for example, linear velocity and angular velocity, but the present disclosure is not limited thereto.

[0079] Specifically, the lateral offset e between the autonomous mobile device 100 and the target point T lat is, for example, related to the orientation of the target point T More specifically, the lateral offset e lat is used to measure the offset between the position of the autonomous mobile device 100 and the orientation of the target point T Therefore, the lateral offset e between the autonomous mobile device 100 and the target point T lat is, for example, more related to the position of the autonomous mobile device 100.

[0080] In some embodiments, the lateral offset e lat is, for example, related to the angle θ between the line connecting the autonomous mobile device 100 and the target point T and the orientation of the target point T For example, the lateral offset e lat can be related to θ. For example, the lateral offset e lat can be related to sinθ.

[0081] In some embodiments, as Figure 3 shown, the lateral offset e between the autonomous mobile device 100 and the target point T lat is, for example, the distance from the autonomous mobile device 100 to the straight line L, where the straight line L passes through the target point T and is parallel to the orientation of the target point T and passes through the target point T and is parallel to the orientation of the target point T

[0082] In some embodiments, the path curvature κ of the motion trajectory can be expressed, for example, by the following formula (1):

[0083]

[0084] where, For example, it is a vector pointing from the autonomous mobile device 100 to the target point T; For example, it is the distance between the autonomous mobile device 100 and the target point T (for the sake of simplicity, it is also denoted as r in this text); δ is, for example, the angle from to the orientation of the autonomous mobile device 100; θ is, for example, the angle from to the orientation to the target point T.

[0085] Among them, the function f1(δ,θ) is determined according to the adopted motion control law, for example. Those skilled in the art can implement it based on requirements. The embodiments of the present disclosure do not limit the motion control law adopted in specific implementations here.

[0086] In particular, in Equation (1), the coefficient of the inverse proportional function [f1(δ,θ)+f2(e lat )] includes a term f2(e lat ) related to the lateral offset e between the autonomous mobile device 100 and the target point T lat ). In some examples, the term f2(e lat ) is, for example, a function positively correlated with the lateral offset e lat . In some examples, the term f2(e lat ) is, for example, a function proportional to the lateral offset e lat , such as k*e lat , and the constant k is a positive value.

[0087] In some embodiments, the path curvature κ of the motion trajectory is determined by a motion control law based on the Lyapunov function, for example. Taking Figure 3 as an example, the motion of the autonomous mobile device 100 can be expressed as the following Equation (2):

[0088]

[0089] Among them, the dot symbol is used to represent the derivative with respect to time.

[0090] According to the motion control law (for example, Jong Jin Park, Benjamin Kuipers published in 2011 (The motion control law in the paper "A Smooth Control Law for Graceful Motion of Differential Wheeled Mobile Robots in 2D Environment" of the 20XX IEEE International Conference on Robotics and Automation). Starting from the motion of the autonomous mobile device 100 (e.g., Equation (2)), based on the Lyapunov function candidate V of Equation (3) below and the virtual control parameter δ of Equation (4) below, the control law of the angular velocity ω represented by the following Equation (5) can be obtained.

[0091]

[0092] δ = tan -1 (-k1θ)… (4)

[0093]

[0094] where z is defined as δ - tan -1 (-k1θ), for example, and k1, k2 are constants, for example.

[0095] To improve the alignment smoothness between the autonomous mobile device 100 and the target point T, the embodiments of the present disclosure make the coefficient of the inverse proportional function of the path curvature include a term related to the lateral offset e lat of the function. Therefore, the above Equation (5) is adjusted to the following Equation (6)

[0096]

[0097] where e lat is the lateral offset between the autonomous mobile device 100 and the target point T, for example, and k3 is a constant, for example.

[0098] Next, since the angular velocity ω is a linear function of the linear velocity v (e.g., ω = κ(r,θ,δ)*v), therefore, the path curvature κ of the following Equation (7) can be determined based on the above Equation (6).

[0099]

[0100] Based on the above, when determining the motion control parameters, the controller 120 determines the linear velocity v, for example. It should be noted that the present disclosure does not limit the way of determining the linear velocity v here, and those skilled in the art can set it according to their needs. In some examples, the linear velocity v can be determined as a constant value. In some examples, the linear velocity v is a function of the distance between the autonomous mobile device 100 and the target point T, for example, and can be valued according to the current relative attitude.

[0101] When determining the motion control parameters, the controller 120 calculates the current curvature based on, for example, the path curvature derived from the motion control law.

[0102] For example, the controller 120 can obtain the current distance between the autonomous mobile device 100 and the target point T (such as, but not limited to, based on the current relative pose of the foregoing embodiment), the current orientation of the autonomous mobile device 100 (such as, but not limited to, based on the current device pose of the foregoing embodiment), and the current orientation of the target point T (such as, but not limited to, based on the current relative pose and / or current device pose of the foregoing embodiment) through the sensor system 130, and then uses the path curvature derived from the motion control law (such as, but not limited to, Equation (1) or Equation (7)) to calculate the current curvature. When determining the motion control parameters, the controller 120 calculates the angular velocity based on the pre-obtained linear velocity and the current curvature according to the linear function relationship between the angular velocity and the linear velocity (such as, ω = κ * v).

[0103] Based on the determined motion control parameters of the autonomous mobile device 100, the controller 120 can control the drive system 110 to control the autonomous mobile device 100 to move along the motion trajectory.

[0104] Please return to

[0105] In operation 408, the controller 120 determines whether to stop the motion of the autonomous mobile device 100. If the controller 120 determines to stop the motion of the autonomous mobile device 100, it proceeds to operation 410; otherwise, if the controller 120 determines not to stop the motion of the autonomous mobile device 100, it returns to operation 402. Figure 4 In some embodiments, the controller 120 determines, for example, whether the autonomous mobile device 100 is aligned with the target point T. If it is determined that the alignment is completed, it proceeds to operation 410 to stop the motion of the autonomous mobile device 100; otherwise, if it is determined that the alignment is not completed, it does not stop the motion of the autonomous mobile device 100 and returns to operation 402.

[0106]

[0107] ​Specifically, the controller 120, for example, will determine the attitude difference between the autonomous mobile device 100 and the target point T, and based on this attitude difference, determine whether the alignment is completed to decide whether to stop the autonomous mobile device 100. For example, the controller 120 can set a distance threshold. When the current distance between the autonomous mobile device 100 and the target point T is less than or equal to the set distance threshold (for example, but not limited to, based on the current relative attitude of the foregoing embodiment), it is determined that the alignment is completed and the autonomous mobile device 100 is stopped. For example, the controller 120 can set a distance threshold and an angle threshold. When the current distance between the autonomous mobile device 100 and the target point T is less than or equal to the set distance threshold, and the included angle between the orientation of the autonomous mobile device 100 and the orientation of the target point T is less than or equal to the set angle threshold (for example, but not limited to, based on the current relative attitude of the foregoing embodiment), it is determined that the alignment is completed and the autonomous mobile device 100 is stopped.

[0108] It is worth mentioning that after stopping the autonomous mobile device 100, since the speed of the autonomous mobile device is 0 and the distance from the target point T is relatively close, if the attitude of the target point T is obtained again through the sensor system 130 (for example, including a camera and / or lidar) at this time, a higher accuracy can be achieved.

[0109] Figure 6 The flowchart of attitude error correction according to an embodiment of the present disclosure is illustrated.

[0110] In some embodiments, after stopping the autonomous mobile device 100 by operation 410, in operation 602 the controller 120 will reacquire the attitude of the target point T through the sensor system 130. For example, the controller 120 will, after stopping the autonomous mobile device 100, use Figure 5 the method introduced in the embodiment shown, and reacquire the attitude of the target point T within a preset time (for example, but not limited to, 10 seconds). For example, during the process of reacquiring the attitude of the target point T, the data of the attitude of the target point T obtained before the autonomous mobile device 100 stops is not considered.

[0111] Advantageously, the attitude of the target point T reacquired in operation 602 can have higher accuracy, which is suitable for further correcting the attitude error of the alignment between the autonomous mobile device 100 and the target point T.

[0112] In operation 604, the controller 120 will correct the attitude error of the autonomous mobile device 100 based on the reacquired attitude of the target point T.

[0113] Figures 7A to 7C The schematic diagram of attitude error correction according to an embodiment of the present disclosure is illustrated.

[0114] Please refer to first Figure 7A , the attitude error between the autonomous mobile device 100 and the target point T includes at least one of the lateral error ERR lat , the longitudinal error ERR long , and the angular error ERR ori .

[0115] Specifically, the lateral error ERR lat is, for example, the distance from the autonomous mobile device 100 to the straight line L , where the straight line L passes through the target point T and is parallel to the orientation of the target point T

[0116] Specifically, the longitudinal error ERR long is, for example, the distance between the autonomous mobile device 100 and the target point T after the autonomous mobile device 100 is translated along the lateral error ERR lat onto the straight line L

[0117] Specifically, the angular error ERR ori is, for example, the included angle between the orientation of the autonomous mobile device 100 and the orientation of the target point T

[0118] It should be noted that the present disclosure does not limit the specific correction method when performing attitude error correction herein, and those skilled in the art can design it according to their needs

[0119] Please refer to Figures 7A to 7C , in some examples, based on Figure 5 the method of the embodiment, the autonomous mobile device 100 can first correct the lateral error ERR lat (as Figure 7A shown, the autonomous mobile device 100 moves linearly to the straight line L to become the autonomous mobile device 100'), then correct the angular error (as Figure 7B shown, the autonomous mobile device 100 turns by an angle of φ = Err ori to be in the same direction as the orientation of the target point T to become the autonomous mobile device 100'), and finally correct the longitudinal error (as Figure 7C shown, the autonomous mobile device 100 moves along the straight line L to the target point T to become the autonomous mobile device 100')

[0120] In summary, for the autonomous mobile device and its control method proposed in the present disclosure, by adjusting the algorithm used in path calculation, the lateral offset between itself and the target point can be corrected more quickly, improving the alignment smoothness and efficiency between the autonomous mobile device and the target point. In addition, by performing coordinate transformation and averaging on the data obtained by the sensor system at multiple time points, the problems caused by insufficient stability of the sensor system can be effectively solved. Furthermore, the embodiments of the present disclosure can further correct errors by utilizing the characteristics of the sensor system itself after the alignment is completed and stopped, further improving the accuracy.

[0121] Based on the above description, it is obvious that various techniques can be used to implement the concepts described in this application without departing from the scope of these concepts. In addition, although the concepts have been specifically described with reference to certain embodiments, those skilled in the art will recognize that changes can be made in form and detail without departing from the scope of these concepts. Thus, the described embodiments will be considered illustrative rather than restrictive in all respects. Moreover, it should be understood that this application is not limited to the specific embodiments described above, but many rearrangements, modifications, and substitutions can be made without departing from the scope of the present disclosure.

Claims

1. A control method for an autonomous mobile device, characterized in that, The control method includes: Obtaining the pose of a target point; Determining motion control parameters based on the pose of the target point; and Controlling the autonomous mobile device to move along a motion trajectory according to the motion control parameters, where the path curvature of the motion trajectory includes an inverse proportional function of the distance between the autonomous mobile device and the target point, the coefficient of the inverse proportional function includes a term related to the lateral offset between the autonomous mobile device and the target point, and the lateral offset is related to the orientation of the target point.

2. The control method according to claim 1, characterized in that The lateral offset is also related to the position of the autonomous mobile device.

3. The control method according to claim 1, wherein, The action of obtaining the pose of the target point includes: Obtaining multiple target poses of the target point at multiple time points through a sensor system; and Calculating a weighted average of the multiple target poses to obtain the current target pose.

4. The control method according to claim 3, characterized in that, The action of obtaining the multiple target poses of the target point at the multiple time points through the sensor system includes: Detecting the target point through the sensor system to obtain a sensing result; and Converting the sensing result into an odometry coordinate system to obtain one of the multiple target poses.

5. The control method according to claim 4, characterized in that The control method further includes: Detecting the motion of the autonomous mobile device through the sensor system; Calculating the current device pose of the autonomous mobile device in the odometry coordinate system based on the motion; and Calculating the current relative pose between the target point and the autonomous mobile device based on the current target pose and the current device pose.

6. The control method according to claim 3, wherein The multiple target poses at the multiple time points include a first target pose at a first time point, the first target pose is detected and obtained by a camera on the autonomous mobile device, and the weight corresponding to the first target pose is negatively correlated with the speed of the autonomous mobile device at the first time point.

7. The control method according to claim 3, wherein The multiple target poses at the multiple time points include a first target pose at a first time point, the first target pose is detected and obtained by a lidar on the autonomous mobile device, and the weight corresponding to the first target pose is negatively correlated with the distance between the target point and the autonomous mobile device.

8. The control method according to claim 1, wherein It further includes: Judging the pose difference between the autonomous mobile device and the target point; Deciding whether to stop the autonomous mobile device based on the pose difference; After stopping the autonomous mobile device, reacquiring the pose of the target point through the sensor system; And Correcting the pose error of the autonomous mobile device based on the reacquired pose of the target point, where the pose error includes at least one of a lateral error, a longitudinal error, and an angular error.

9. The control method according to claim 1, wherein The motion control parameters include a linear velocity and an angular velocity, and determining the motion control parameters based on the pose of the target point includes: Determining the linear velocity; Calculating the current curvature based on the current distance between the autonomous mobile device and the target point, the current orientation of the autonomous mobile device, and the current orientation of the target point; and Calculating the angular velocity based on the linear velocity and the current curvature.

10. The control method according to claim 1, wherein the autonomous mobile device includes a Non-Omnidirectional Drive system.

11. An autonomous mobile device, characterized in that, Comprising: A drive system; And A controller, coupled to the drive system, and configured to: Obtain the pose of a target point; Determine motion control parameters based on the pose of the target point; And Control the autonomous mobile device to move along a motion trajectory according to the motion control parameters, wherein the path curvature of the motion trajectory includes an inverse function of the distance between the autonomous mobile device and the target point, the coefficient of the inverse function includes a term related to the lateral offset between the autonomous mobile device and the target point, and the lateral offset is related to the orientation of the target point.

12. The autonomous mobile device according to claim 11, wherein The lateral offset is further related to the position of the autonomous mobile device.

13. The autonomous mobile device according to claim 11, characterized in that, It further includes a sensor system, wherein obtaining the pose of the target point includes: Obtaining a plurality of target poses of the target point at a plurality of time points through the sensor system; and Calculating a weighted average of the plurality of target poses to obtain the current target pose.

14. The autonomous mobile device according to claim 13, wherein, Obtaining the plurality of target poses of the target point at the plurality of time points through the sensor system includes: Detecting the target point through the sensor system to obtain a sensing result; and Converting the sensing result into an odometry coordinate system to obtain one of the plurality of target poses.

15. The autonomous mobile device according to claim 14, wherein, The controller is further configured to: Detect the motion of the autonomous mobile device through the sensor system; Calculate the current device pose of the autonomous mobile device in the odometry coordinate system based on the motion; And Calculate the current relative pose between the target point and the autonomous mobile device based on the current target pose and the current device pose.

16. The autonomous mobile device according to claim 13, wherein Wherein the plurality of target poses at the plurality of time points include a first target pose at a first time point, the first target pose is detected and obtained by a camera on the autonomous mobile device, and the weight corresponding to the first target pose is negatively correlated with the speed of the autonomous mobile device at the first time point.

17. The autonomous mobile device according to claim 13, wherein The plurality of target poses at the plurality of time points include a first target pose at a first time point, the first target pose is detected and obtained by a lidar on the autonomous mobile device, and the weight corresponding to the first target pose is negatively correlated with the distance between the target point and the autonomous mobile device.

18. The autonomous mobile device according to claim 11, characterized in that, It further includes a sensor system, wherein the controller is further configured to: Judge the pose difference between the autonomous mobile device and the target point; Determine whether to stop the autonomous mobile device based on the pose difference; After stopping the autonomous mobile device, re-obtain the pose of the target point through the sensor system; And Correct the pose error of the autonomous mobile device based on the re-obtained pose of the target point, wherein the pose error includes at least one of a lateral error, a longitudinal error, and an angular error.

19. The autonomous mobile device according to claim 11, wherein Wherein the motion control parameters include a linear velocity and an angular velocity, and determining the motion control parameters based on the pose of the target point includes: Determining the linear velocity; Calculate a current curvature based on a current distance between the autonomous mobile device and the target point, a current orientation of the autonomous mobile device, and a current orientation of the target point; and Calculate the angular velocity based on the linear velocity and the current curvature.

20. The autonomous mobile device according to claim 11, wherein The drive system includes a Non-Omnidirectional Drive system.

Images