Control method and device of a mobility robot, mobility robot and storage medium

Abstract

The application discloses a control method and device of a walking robot, the walking robot and a storage medium, relates to the field of walking robots, and the control method of the walking robot comprises the following steps: acquiring a handle operation amount of the walking robot, and determining a target driving parameter corresponding to the handle operation amount based on a preset nonlinear mapping relationship; controlling the walking robot based on the target driving parameter, and acquiring an actual driving parameter; and updating the preset nonlinear mapping relationship based on the difference between the actual driving parameter and the target driving parameter. The application adopts the nonlinear mapping relationship to determine the target driving parameter of the walking robot, can adapt to more complex scenes, and can also update and adjust the nonlinear mapping relationship according to the actual driving parameter and the target driving parameter, so that the applicability is better.

Description

Technical Field

[0001] This application relates to the technical field of personal mobility robots, and in particular to a control method, device, personal mobility robot, and storage medium for a personal mobility robot. Background Technology

[0002] Personal mobility robots, including smart wheelchairs and smart mobility scooters, are products that require control handles for movement. In related technologies, the control handles for these robots are mostly linear handles, which convert the input of the handle into driving parameters using a linear ratio to control the robot. From a user experience perspective, linear handle systems have significant shortcomings in sensitivity adjustment. In low-speed scenarios, such as adjusting position in confined spaces, the user needs the wheelchair to respond precisely to even the smallest handle inputs. However, the linear system's poor sensitivity in these situations leads to imprecise control and difficulty in achieving fine-tuned position adjustments. Conversely, when the wheelchair is traveling at high speeds, the linear system lacks effective buffering and limitation for larger changes in handle input, resulting in low error tolerance. Even slight deviations in user input can cause significant changes in the wheelchair's speed or direction, posing safety hazards and increasing the risk of misoperation. This is especially problematic for users with weak upper limb strength and poor fine motor control, such as stroke rehabilitation patients and the elderly, where linear handle systems are difficult to operate and offer a poor user experience.

[0003] Considering the operational characteristics of wheelchairs under different working conditions, linear control strategies are ill-suited to complex and ever-changing situations. Under varying load conditions, such as significant differences in rider weight or the wheelchair carrying items of varying weights, the wheelchair's dynamic characteristics change significantly. Furthermore, the required driving force and speed control methods differ drastically depending on the terrain, such as flat indoor floors, slightly undulating outdoor surfaces, and slopes. Because linear handle systems cannot automatically adjust control parameters according to these real-time changes, the wheelchair's performance becomes unstable under different conditions, potentially affecting both driving efficiency and user safety. For example, when climbing hills, the linear system may fail to provide sufficient power, resulting in insufficient wheelchair power; conversely, when traveling on bumpy roads, it struggles to effectively suppress vibrations, impacting riding comfort. Summary of the Invention

[0004] Therefore, the purpose of this application is to provide a control method, device, robot, and storage medium for a personal mobility robot. This application uses a nonlinear mapping relationship to determine the target driving parameters of the personal mobility robot through the operation of the handle, which can adapt to more complex scenarios. Furthermore, the nonlinear mapping relationship can be updated and adjusted according to the actual driving parameters and the target driving parameters, making it suitable for various working conditions and with better applicability.

[0005] This application provides a control method for a personal mobility robot. The method includes: acquiring the handle operation amount of the personal mobility robot, and determining a target driving parameter corresponding to the handle operation amount based on a preset nonlinear mapping relationship; controlling the personal mobility robot based on the target driving parameter, and acquiring actual driving parameters; and updating the preset nonlinear mapping relationship based on the difference between the actual driving parameter and the target driving parameter.

[0006] For example, the handle operation amount includes a first operation amount in a first direction, and the target driving parameter includes a target speed; determining the target driving parameter corresponding to the handle operation amount based on a preset nonlinear mapping relationship includes: determining the mapping relationship between the target speed or the change in the target speed and the first operation amount according to different preset intervals in which the first operation amount is located.

[0007] For example, determining the linear relationship between the target speed or the change in the target speed and the first operation amount based on different preset intervals in which the first operation amount is located includes: when the first operation amount is greater than a first preset value and less than or equal to a second preset value, determining that the change in the target speed increases linearly with the first operation amount; when the first operation amount is greater than the second preset value and less than or equal to a third preset value, determining that the target speed increases linearly with the first operation amount; when the first operation amount is greater than the third preset value and less than or equal to a fourth preset value, determining that the change in the target speed decreases linearly with the first operation amount; when the first operation amount is greater than the fourth preset value and less than or equal to a fifth preset value, determining that the target speed is the maximum speed; when the first operation amount is less than the first preset value and greater than or equal to a sixth preset value, determining that the change in the target speed increases linearly with the first operation amount; when the first operation amount is less than the sixth preset value and greater than or equal to a seventh preset value, determining that the target speed decreases linearly with the first operation amount; and when the first operation amount is less than the seventh preset value and greater than or equal to an eighth preset value, determining that the change in the target speed decreases linearly with the first operation amount.

[0008] For example, the handle operation amount includes a second operation amount in a second direction, the target driving parameter includes a target angular velocity, and the step of determining the target driving parameter corresponding to the handle operation amount based on a preset nonlinear mapping relationship includes: when the second operation amount is greater than a first preset value and less than or equal to a ninth preset value, determining the target angular velocity corresponding to the handle operation amount based on an exponential mapping relationship, wherein the exponent base of the exponential mapping relationship is greater than an integer 1; when the second operation amount is greater than the ninth preset value and less than or equal to a tenth preset value, determining the target angular velocity corresponding to the handle operation amount based on a logarithmic mapping relationship, wherein the logarithmic base of the logarithmic mapping relationship is greater than an integer 1.

[0009] For example, controlling the personal mobility robot based on the target driving parameters includes: dividing the target speed into low speed threshold, medium speed threshold and high speed threshold, and performing segmented control on the personal mobility robot.

[0010] For example, the segmented control of the personal mobility robot includes: when the target speed is greater than the low speed threshold and less than or equal to the middle speed threshold, controlling the personal mobility robot to perform an acceleration operation and maintain it for a first preset time; when the target speed is greater than the middle speed threshold and less than or equal to the high speed threshold, controlling the personal mobility robot to perform a uniform acceleration operation and maintain it for a second preset time; and when the target speed is greater than the high speed threshold, controlling the personal mobility robot to perform a deceleration operation and maintain it for a third preset time.

[0011] For example, the actual driving parameters include the current speed; the difference between the actual driving parameters and the target driving parameters includes the speed deviation and the rate of change of the speed deviation between the current speed and the target speed; updating the preset nonlinear mapping relationship based on the difference between the actual driving parameters and the target driving parameters includes: updating at least one of the low speed threshold, the medium speed threshold, the high speed threshold, the first preset time, the second preset time, and the third preset time based on the different preset intervals in which the speed deviation and the rate of change of the speed deviation are located.

[0012] For example, updating at least one of the low speed threshold, the medium speed threshold, the high speed threshold, the first preset time, the second preset time, and the third preset time based on different preset intervals of the speed deviation and the rate of change of the speed deviation includes: when the speed deviation is greater than a first deviation threshold and the rate of change of the speed deviation is greater than zero and less than a first rate of change threshold, decreasing the low speed threshold and / or increasing the first preset time; when the speed deviation approaches zero and the rate of change of the speed deviation approaches zero, increasing the medium speed threshold and / or increasing the high speed threshold and / or decreasing the first preset time; when the speed deviation approaches zero and the rate of change of the speed deviation approaches zero, increasing the medium speed threshold and / or increasing the high speed threshold and / or decreasing the first preset time; when the speed deviation... When the speed deviation is less than zero and greater than a second deviation threshold, and the rate of change of the speed deviation is less than zero and greater than a second rate of change threshold, the first preset time is reduced; when the speed deviation is greater than zero and less than a third deviation threshold, and the rate of change of the speed deviation is less than a third rate of change threshold, the speed threshold is reduced, and / or the third preset time is increased; when the speed deviation is less than a fourth deviation threshold and the rate of change of the speed deviation is less than the third rate of change threshold, the third preset time is reduced; wherein, the first deviation threshold > the third deviation threshold > zero > the second deviation threshold > the fourth deviation threshold; the first rate of change threshold > zero > the second rate of change threshold > the third rate of change threshold.

[0013] For example, controlling the personal mobility robot based on the target driving parameters includes: when the target angular velocity is less than or equal to an angular velocity threshold, accelerating the personal mobility robot according to an exponential mode, wherein the exponent base of the exponential mode is greater than an integer 1; and when the target angular velocity is greater than the angular velocity threshold, accelerating the personal mobility robot according to a logarithmic mode, wherein the logarithmic base of the logarithmic mode is greater than an integer 1.

[0014] For example, the actual driving parameters include the current angular velocity; the difference between the actual driving parameters and the target driving parameters includes the angular velocity deviation and the rate of change of the angular velocity deviation between the current angular velocity and the target angular velocity; updating the preset nonlinear mapping relationship based on the difference between the actual driving parameters and the target driving parameters includes: when the angular velocity deviation is greater than a fifth deviation threshold, and the rate of change of the angular velocity deviation is greater than zero and less than a fourth rate of change threshold, and / or, when the angular velocity deviation is less than zero and greater than a sixth deviation threshold, and the rate of change of the angular velocity deviation is less than zero and greater than a fifth rate of change threshold... When the value is less than the seventh deviation threshold and the rate of change of the velocity deviation is less than the sixth rate of change threshold, the exponential parameter of the exponential mode is increased; when the angular velocity deviation approaches zero and the rate of change of the angular velocity deviation approaches zero, and / or when the angular velocity deviation is greater than zero and less than the eighth deviation threshold and the rate of change of the velocity deviation is less than the sixth rate of change threshold, the system switches to the logarithmic mode; wherein the fifth deviation threshold > the eighth deviation threshold > zero > the sixth deviation threshold > the seventh deviation threshold; and the fourth rate of change threshold > zero > the fifth rate of change threshold > the sixth rate of change threshold.

[0015] Another embodiment of this application provides a control device for a personal mobility robot. The device includes: a determining module, configured to acquire the handle operation amount of the personal mobility robot and determine a target driving parameter corresponding to the handle operation amount based on a preset nonlinear mapping relationship; a control module, configured to control the personal mobility robot based on the target driving parameter and acquire actual driving parameters; and an updating module, configured to update the preset nonlinear mapping relationship based on the difference between the actual driving parameter and the target driving parameter.

[0016] Another embodiment of this application provides a personal mobility robot, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described control method for the personal mobility robot.

[0017] Another embodiment of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described control method for a personal mobility robot.

[0018] In the above embodiments, the control method for the personal mobility robot includes: acquiring the handle operation amount of the personal mobility robot, and determining the target driving parameters corresponding to the handle operation amount based on a preset nonlinear mapping relationship; controlling the personal mobility robot based on the target driving parameters, and acquiring the actual driving parameters; and updating the preset nonlinear mapping relationship based on the difference between the actual driving parameters and the target driving parameters. This invention uses a nonlinear mapping relationship to determine the target driving parameters of the personal mobility robot, which can adapt to more complex scenarios. Furthermore, the nonlinear mapping relationship can be updated and adjusted according to the actual driving parameters and the target driving parameters, making it suitable for various working conditions and offering better applicability. Attached Figure Description

[0019] Figure 1 A flowchart illustrating the control method for the personal mobility robot provided in this application embodiment; Figure 2 A schematic diagram of the control device for the personal mobility robot provided in an embodiment of this application; Figure 3 A block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0020] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0021] Figure 1 This is a flowchart of a control method for a personal mobility robot according to an embodiment of this application.

[0022] As an example, such as Figure 1 As shown, the control method for the personal mobility robot includes: S101, acquire the handle operation amount of the mobility robot, and determine the target driving parameters corresponding to the handle operation amount based on the preset nonlinear mapping relationship.

[0023] S102 controls the personal mobility robot based on the target driving parameters and obtains the actual driving parameters.

[0024] S103, update the preset nonlinear mapping relationship based on the difference between the actual driving parameters and the target driving parameters.

[0025] For example, the mobility robot can be a smart wheelchair, a smart mobility scooter, etc., and is equipped with a handle for user operation. The mobility robot includes a data acquisition device connected to the handle, used to collect the handle operation inputs and quantify them. This application proposes a preset nonlinear mapping relationship to map different target driving parameters to different handle operation inputs. Target driving parameters include, for example, parameters such as speed and angular velocity. The mobility robot controller controls the mobility robot according to the target driving parameters. During the operation of the mobility robot, actual driving parameters, such as actual driving speed, are collected. This application also updates the preset nonlinear mapping relationship based on the difference between the actual driving parameters and the target driving parameters.

[0026] The control method of the personal mobility robot in this application uses a nonlinear mapping relationship to determine the target driving parameters of the personal mobility robot through the operation of the handle. It can adapt to more complex scenarios, and the nonlinear mapping relationship can be updated and adjusted according to the actual driving parameters and the target driving parameters. It is applicable to a variety of working conditions and has better applicability.

[0027] As an example, the controller input includes a first input in a first direction, and the target driving parameter includes a target speed; the target driving parameter corresponding to the controller input is determined based on a preset nonlinear mapping relationship, including: Based on the different preset intervals in which the first operational quantity is located, the mapping relationship between the target speed or the change in the target speed and the first operational quantity is determined respectively.

[0028] For example, the first direction can be the X-axis, with the forward and backward movement of the handle as the X-axis. It can be understood that the first operational quantity in the first direction is the amount of forward and backward movement of the handle. Of course, if the handle is pushed at an angle, the component of the angled pushing operation in the X-axis direction is used as the first operational quantity in the first direction. The target driving parameters include the target speed, and the preset nonlinear mapping relationship includes a mapping relationship characterizing the first operational quantity and the target speed. This application divides the first operational quantity in the first direction into multiple preset intervals. In different preset intervals, there are different mapping relationships between the target speed or the change in target speed and the first operational quantity. The mapping relationship of each interval is described in detail below.

[0029] As an example, when the first operation amount is greater than the first preset value and less than or equal to the second preset value, it is determined that the change in the target speed increases linearly with the first operation amount; When the first operation amount is greater than the second preset value and less than or equal to the third preset value, the target speed is determined to increase linearly with the first operation amount. When the first operation amount is greater than the third preset value and less than or equal to the fourth preset value, the change in the target speed is determined to decrease linearly with the first operation amount. When the first operation amount is greater than the fourth preset value and less than or equal to the fifth preset value, the target speed is determined to be the maximum speed. When the first operation amount is less than the first preset value and greater than or equal to the sixth preset value, it is determined that the change in the target speed increases linearly with the first operation amount. When the first operation amount is less than the sixth preset value and greater than or equal to the seventh preset value, the target speed is determined to decrease linearly with the first operation amount. When the first operation amount is less than the seventh preset value and greater than or equal to the eighth preset value, the change in the target speed is determined to decrease linearly with the first operation amount.

[0030] For example, when the first operation amount is greater than a first preset value and less than or equal to a second preset value, the change in target speed is determined to increase linearly with the first operation amount. The first preset value can be zero or a low threshold, and the second preset value is greater than the first preset value. It can be understood that at this time, the first operation amount is small, and it is in the initial stage. For example, a user gently pushes the handle forward to start the mobility robot or the user fine-tunes the position in a narrow space. In this scenario, the mobility robot needs to be able to respond accurately to tiny handle operations, and the change in target speed is determined to increase linearly with the first operation amount, that is, the acceleration increases linearly from zero, and the target speed increases rapidly. In this application, when the first operation amount is small, the target speed increases rapidly, which enables accurate response to tiny handle operations, increases the precision of control, and achieves fine position adjustment.

[0031] For example, when the first operation amount is greater than the second preset value and less than or equal to the third preset value, the target speed is determined to increase linearly with the first operation amount. The third preset value is greater than the second preset value, which can be understood as the first operation amount increasing slightly at this time. To ensure the robot can operate in a steady state, the target speed is determined to increase linearly with the first operation amount, that is, to accelerate at a constant maximum acceleration.

[0032] For example, when the first operation amount is greater than the third preset value and less than or equal to the fourth preset value, the change in target speed is determined to decrease linearly with the first operation amount. Since the fourth preset value is greater than the third preset value, it is understood that the first operation amount is relatively large, and the speed increase should not be too rapid; otherwise, the error tolerance will be low. Even a slight deviation in the user's operation could cause a significant change in the wheelchair's speed or direction, posing a safety hazard and increasing the risk of misoperation. Considering this scenario, this application determines that the change in target speed decreases linearly with the first operation amount, i.e., the acceleration decreases linearly until it reaches 0. This application effectively buffers and limits the change in the first operation amount when the target speed of the mobility robot is too large, ensuring user safety.

[0033] For example, when the first operation amount is greater than the fourth preset value and less than or equal to the fifth preset value, the target speed is determined to be the maximum speed. The fifth preset value is greater than the fourth preset value because in the previous stage, when the acceleration linearly decreased to 0, the maximum speed of the mobility robot was reached. At this time, no matter how the first operation amount increases, the target speed will always be the maximum speed.

[0034] For example, when the first operation amount is less than a first preset value but greater than or equal to a sixth preset value, the change in target speed is determined to increase linearly with the first operation amount. The sixth preset value is less than the first preset value, which can be understood as a negative number. Within this range, the first operation amount is in the opposite direction to acceleration, for example, the user slightly pushes the handle backward in the X direction. At this time, deceleration is required, and the change in target speed is determined to increase linearly with the first operation amount. The change in target speed is the acceleration. It can be understood that as the first operation amount increases in the opposite direction, the acceleration also increases linearly in the opposite direction. Macroscopically, the target speed decays more rapidly with the first operation amount, enabling a quick response to the user's deceleration needs to prevent the occurrence of sudden events and ensure user safety.

[0035] For example, when the first operation amount is less than the sixth preset value and greater than or equal to the seventh preset value, it is determined that the target speed decreases linearly with the first operation amount. The seventh preset value is less than the sixth preset value. For example, the user is still pushing the handle backward, but the amplitude increases slightly. At this time, it is necessary to decelerate smoothly. It is determined that the target speed decreases linearly with the first operation amount. It can be understood that when the first operation amount increases in the opposite direction, the acceleration remains unchanged, and the target speed decreases linearly in the opposite direction of the first operation amount.

[0036] For example, when the first operation amount is less than the seventh preset value but greater than or equal to the eighth preset value, the change in target speed is determined to decrease linearly with the first operation amount. If the eighth preset value is less than the seventh preset value, for example, if the user pushes the handle backward with a large amplitude, the target speed has already decreased to a small range. For comfort considerations, the target speed can then decrease slowly with the first operation amount, and the change in target speed is determined to decrease linearly with the first operation amount. That is, the acceleration decreases linearly in the opposite direction with the first operation amount to 0, so that the target speed decreases smoothly to 0, ensuring the user's comfort in the later stages of deceleration.

[0037] For example, for the first operation in the X direction, an S-curve velocity planning algorithm is introduced during the start-up, acceleration, deceleration, and braking processes. Overall, acceleration is divided into seven stages: Acceleration stage: Acceleration increases linearly from 0; Uniform acceleration stage: Acceleration at a constant maximum acceleration; Deceleration stage: Acceleration decreases linearly to 0; Uniform speed stage: Running at a constant maximum speed; Acceleration / deceleration stage: Acceleration increases linearly in the opposite direction (deceleration begins); Uniform deceleration stage: Deceleration decreases linearly to 0.

[0038] This application divides the first operation quantity and matches different mapping relationships for different intervals, taking into account various situations in the actual application scenarios of the mobility robot, making it applicable to various working conditions and balancing response accuracy and safety.

[0039] As an example, the controller input includes a second input in the second direction, and the target driving parameters include the target angular velocity. The target driving parameters corresponding to the controller input are determined based on a preset nonlinear mapping relationship, including: When the second operation amount is greater than the first preset value and less than or equal to the ninth preset value, the target angular velocity corresponding to the handle operation amount is determined based on the exponential mapping relationship, wherein the exponent base of the exponential mapping relationship is greater than an integer 1; When the second operation amount is greater than the ninth preset value and less than or equal to the tenth preset value, the target angular velocity corresponding to the handle operation amount is determined based on the logarithmic mapping relationship, wherein the logarithmic base of the logarithmic mapping relationship is greater than the integer 1.

[0040] For example, the second direction can be the Y-direction, with the left-right direction of the handle as the Y-axis direction, perpendicular to the first direction. It can be understood that the second operational quantity in the second direction is the amount of pushing the handle left or right. Of course, if the handle is pushed diagonally, the component of the diagonal pushing operation in the Y-axis direction is used as the second operational quantity in the second direction. The target driving parameters include the target angular velocity, and the preset nonlinear mapping relationship includes a mapping relationship characterizing the second operational quantity and the target angular velocity. This application divides the second operational quantity in the second direction into multiple intervals, with different mapping relationships corresponding to different intervals. The mapping relationship for each interval is described in detail below.

[0041] For example, when the second operation amount is greater than the first preset value and less than or equal to the ninth preset value, the target angular velocity corresponding to the handle operation amount is determined based on an exponential mapping relationship. The first preset value can be zero or a low threshold. The ninth preset value is greater than the first preset value, which indicates that the second operation amount is relatively small, for example, the user gently pushes the handle to the right to turn. In this scenario, the mobility robot needs to be able to respond accurately to minute handle operations. It is determined that the target angular velocity and the handle operation amount have an exponential mapping relationship, where the exponent base is greater than an integer 1. The larger the exponent base, the more drastic the change in the target angular velocity and the more sensitive the response. The specific exponent base can be determined experimentally to enable the mobility robot to respond accurately to minute handle operations, increasing the precision of control and achieving fine position adjustments.

[0042] For example, when the second operation amount is greater than the ninth preset value and less than or equal to the tenth preset value, the target angular velocity corresponding to the handle operation amount is determined based on a logarithmic mapping relationship. Since the tenth preset value is greater than the ninth preset value, the required angular velocity for the user increases. To prevent over-sensitivity and improve fault tolerance, the target angular velocity and the handle operation amount are determined to have a logarithmic mapping relationship. The logarithmic base of this mapping relationship is greater than the integer 1, and the larger the logarithmic base, the slower the change in the target angular velocity and the better the buffering effect. The specific logarithmic base can be determined experimentally to enable the mobility robot to effectively buffer and limit larger handle operation amounts, thereby improving fault tolerance.

[0043] This application also divides the second operational quantity, matching different mapping relationships for different intervals. Generally, when the Y-direction operational quantity of the handle is small, an exponential growth function is used, enabling the mobility robot to have a high sensitivity response to minute operations at low speeds, facilitating precise control by the user. When the handle operational quantity is large, a logarithmic function is switched to buffer changes in operation, avoiding abrupt changes in wheelchair speed or steering, and improving safety and stability during high-speed travel.

[0044] After determining the target driving parameters based on a preset nonlinear mapping relationship, this application uses the target driving parameters to control the personal mobility robot so that the personal mobility robot can achieve the target driving parameters, such as the target speed and target angular velocity.

[0045] As an example, controlling a personal mobility robot based on target driving parameters includes: dividing the target speed into low, medium, and high speed thresholds, and performing segmented control on the personal mobility robot.

[0046] For example, this application uses thresholds to divide the target speed and performs segmented control on the personal mobility robot. For instance, if the target speed is 5 km / h, the low speed threshold is 1 km / h, the medium speed threshold is 2 km / h, and the high speed threshold is 4 km / h, the 5 km / h speed can be divided into multiple intervals, such as 1-2 km / h, 2-4 km / h, and above 4 km / h, with different control strategies implemented in different intervals.

[0047] As an example, segmented control of a mobility robot includes: When the target speed is greater than the low speed threshold and less than or equal to the middle speed threshold, control the mobility robot to perform an acceleration operation and maintain it for a first preset time. When the target speed is greater than the speed threshold and less than or equal to the speed threshold, control the mobility robot to perform uniform acceleration and maintain it for a second preset time. When the target speed exceeds the high speed threshold, the robot is controlled to decelerate and maintain this speed for a third preset time.

[0048] For example, when the target speed is greater than a low speed threshold and less than or equal to a medium speed threshold, such as when the target speed is between 1-2 km / h, the mobility robot is controlled to perform an acceleration operation and maintain it for a first preset time. This acceleration operation involves increasing acceleration, resulting in a rapid increase in speed, and maintaining this speed for the first preset time. The first preset time can be adjusted; for example, a smaller acceleration results in a longer first preset time, and a larger acceleration results in a shorter first preset time. When the target speed is in the low-speed range, the mobility robot is controlled to perform acceleration operations to respond to the target speed as quickly as possible.

[0049] For example, when the target speed is greater than a mid-speed threshold but less than or equal to a high-speed threshold (e.g., 2-4 km / h), the mobility robot has a certain speed. To maintain steady-state operation, the robot is controlled to perform uniform acceleration and maintain this speed for a second preset time. This second preset time can also be adaptively adjusted. When the target speed is greater than the high-speed threshold, the robot's speed is relatively high. Considering driving safety, the robot is controlled to perform deceleration and maintain this speed for a third preset time. Deceleration indicates a smaller acceleration while the speed increases, which can be understood as a slow increase in speed. This third preset time can also be adaptively adjusted.

[0050] This application implements segmented control of the mobility robot based on the target speed, balancing rapid response at low speeds with stable and safe operation at high speeds, resulting in a better user experience.

[0051] As an example, actual driving parameters include the current speed; the difference between actual driving parameters and target driving parameters includes the speed deviation and the rate of change of the speed deviation between the current speed and the target speed; the preset nonlinear mapping relationship is updated based on the difference between actual driving parameters and target driving parameters, including: Based on the different preset intervals in which the speed deviation and the rate of change of speed deviation are located, at least one of the following is updated: low speed threshold, medium speed threshold, high speed threshold, first preset time, second preset time, and third preset time.

[0052] For example, the personal mobility robot controls its operation according to a target speed, while simultaneously collecting the robot's current speed, the speed deviation between the current speed and the target speed, and the rate of change of the speed deviation. The speed deviation represents the difference between the current speed and the target speed, and the rate of change of the speed deviation represents the degree to which the difference between the current speed and the target speed changes over time. This application updates and adjusts a preset nonlinear mapping relationship based on different preset intervals in which the speed deviation and the rate of change of the speed deviation fall. Specifically, this includes updating and adjusting at least one of a low threshold, a medium threshold, a high threshold, a first preset time, a second preset time, and a third preset time.

[0053] As an example, when the speed deviation is greater than a first deviation threshold and the rate of change of the speed deviation is greater than zero and less than a first rate of change threshold, the speed threshold is reduced, and / or the first preset time is increased; When the speed deviation approaches zero and the rate of change of speed deviation approaches zero, increase the speed threshold, and / or increase the speed threshold, and / or decrease the first preset time. When the speed deviation is less than zero and greater than the second deviation threshold, and the rate of change of the speed deviation is less than zero and greater than the second rate of change threshold, the first preset time is reduced. When the speed deviation is greater than zero and less than the third deviation threshold, and the rate of change of the speed deviation is less than the third rate of change threshold, decrease the high speed threshold and / or increase the third preset time. When the speed deviation is less than the fourth deviation threshold and the rate of change of the speed deviation is less than the third rate of change threshold, reduce the third preset time. Among them, the first deviation threshold > the third deviation threshold > zero > the second deviation threshold > the fourth deviation threshold; the first rate of change threshold > zero > the second rate of change threshold > the third rate of change threshold.

[0054] For example, when the speed deviation is greater than a first deviation threshold and the speed deviation change rate is greater than zero and less than a first change rate threshold, the first deviation threshold can be a positive number and a large value, and the speed deviation change rate can be a positive number and a small value. For example, in the starting stage, the speed deviation is large and the speed deviation change rate is small. At this time, the system control objective is to quickly track the given value, so the speed threshold can be reduced, and / or the first preset time can be increased (increasing the acceleration phase time).

[0055] For example, when the speed deviation approaches zero and the rate of change of the speed deviation approaches zero, for example, in the steady-state operation phase, the system control objective is to operate smoothly. This can be achieved by increasing the speed threshold, and / or increasing the speed high threshold, and / or decreasing the first preset time (reducing the acceleration phase time).

[0056] For example, when the speed deviation is less than zero and greater than the second deviation threshold, and the rate of change of the speed deviation is less than zero and greater than the second rate of change threshold, the second deviation threshold can be negative small or negative medium. Negative small indicates a value with a smaller absolute value and a negative sign. The same applies to negative medium, negative large, positive small, positive medium, and positive large. The second rate of change threshold can also be negative small or negative medium. For example, when the system receives interference, such as when a mobility robot encounters a slightly undulating road surface or slope outdoors, the system control objective is to recover quickly, which can reduce the first preset time (reduce the acceleration phase time).

[0057] For example, when the speed deviation is greater than zero and less than the third deviation threshold, and the speed deviation change rate is less than the third change rate threshold, the third deviation threshold can be positive small or positive medium, and the third change rate threshold can be negative medium or negative large. For example, in a scenario close to the target speed, the control objective of the system is to prevent overshoot, reduce the high speed threshold, and / or increase the third preset time (increase the deceleration period time).

[0058] For example, when the speed deviation is less than the fourth deviation threshold and the speed deviation change rate is less than the third change rate threshold, the fourth deviation threshold can be negative large, and the third change rate threshold can be negative large or negative medium. For example, in a scenario where emergency deceleration is required, the control objective of the system is to brake quickly and reduce the third preset time (reduce the deceleration phase time).

[0059] This application determines the actual application scenario based on speed deviation and the rate of change of speed deviation, and adaptively adjusts the control strategy to meet the scenario requirements. The control method of the mobility robot in this application can be applied to more complex scenarios, has better applicability, and improves the user experience.

[0060] Similar to velocity, this application also divides angular velocity into intervals to achieve segmented control.

[0061] As an example, controlling a mobility robot based on target driving parameters includes: When the target angular velocity is less than or equal to the angular velocity threshold, the acceleration control of the mobility robot is performed according to the exponential mode, where the exponent base of the exponential mode is greater than an integer 1. When the target angular velocity is greater than the angular velocity threshold, the robot is accelerated according to the logarithmic mode, where the logarithmic base is greater than the integer 1.

[0062] For example, when the target angular velocity is less than or equal to the angular velocity threshold, i.e. when the target angular velocity is small, the robot is accelerated in an exponential mode for a rapid response, with the exponent base greater than an integer 1, meaning the angular velocity increases rapidly. When the angular velocity reaches the angular velocity threshold, the robot is accelerated in a logarithmic mode, with the logarithmic base greater than an integer 1, meaning the angular velocity increases slowly.

[0063] As an example, the actual driving parameters include the current angular velocity; the difference between the actual driving parameters and the target driving parameters includes the angular velocity deviation and the rate of change of the angular velocity deviation between the current angular velocity and the target angular velocity; the preset nonlinear mapping relationship is updated based on the difference between the actual driving parameters and the target driving parameters, including: When the angular velocity deviation is greater than the fifth deviation threshold and the rate of change of the angular velocity deviation is greater than zero and less than the fourth rate of change threshold, and / or when the angular velocity deviation is less than zero and greater than the sixth deviation threshold and the rate of change of the angular velocity deviation is less than zero and greater than the fifth rate of change threshold, and / or when the angular velocity deviation is less than the seventh deviation threshold and the rate of change of the velocity deviation is less than the sixth rate of change threshold, the exponential parameter of the exponential mode is increased. When the angular velocity deviation approaches zero and the rate of change of the angular velocity deviation approaches zero, and / or when the angular velocity deviation is greater than zero and less than the eighth deviation threshold, and the rate of change of the velocity deviation is less than the sixth rate of change threshold, switch to logarithmic mode. Among them, the fifth deviation threshold > the eighth deviation threshold > zero > the sixth deviation threshold > the seventh deviation threshold; the fourth rate of change threshold > zero > the fifth rate of change threshold > the sixth rate of change threshold.

[0064] For example, the fifth deviation threshold is positive and large, the fourth rate of change threshold is positive and small, the sixth deviation threshold is negative and small or negative and medium, the fifth rate of change threshold is negative and small or negative and medium, the seventh deviation threshold is negative and large, and the sixth rate of change threshold is negative and large or negative and medium. Similar to speed strategy adjustment, it can be understood that during the start-up phase, and / or the disturbance phase, and / or the emergency deceleration phase, the exponential parameter of the exponential mode is increased to improve the response capability.

[0065] For example, the eighth deviation threshold is positive small or positive medium, and the sixth rate of change threshold is negative medium or negative large. It can be understood that during the steady-state operation phase, and / or, when approaching the target angular velocity phase, the logarithmic mode is switched to prevent overshoot.

[0066] This application also proposes a control device for a personal mobility robot.

[0067] As an example, such as Figure 2 As shown, the control device for the personal mobility robot includes: The determination module 201 is used to acquire the handle operation amount of the mobility robot and determine the target driving parameters corresponding to the handle operation amount based on a preset nonlinear mapping relationship. The control module 202 is used to control the mobility robot based on the target driving parameters and to acquire the actual driving parameters; The update module 203 is used to update the preset nonlinear mapping relationship based on the difference between the actual driving parameters and the target driving parameters.

[0068] This application also proposes a personal mobility robot, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described control method for the personal mobility robot.

[0069] This application also proposes a computer-readable storage medium.

[0070] In this embodiment, a computer program is stored on a computer-readable storage medium, and when the computer program is executed by a processor, it implements the steps of the above-described control method for the personal mobility robot.

[0071] Figure 3 A block diagram of an electronic device provided in an embodiment of this application.

[0072] This application provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described control method for a personal mobility robot.

[0073] like Figure 3 As shown, for ease of understanding, embodiments of this application illustrate a specific electronic device.

[0074] Electronic devices are intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0075] like Figure 3 As shown, the device includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 into a random access memory (RAM) 303. The RAM 303 may also store various programs and data required for the operation of the electronic device. The computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0076] Multiple components in the electronic device are connected to the I / O interface 305. These components include: an input unit 306, such as a keyboard or mouse; an output unit 307, such as various types of displays or speakers; a storage unit 308, such as a disk or optical disk; and a communication unit 309, such as a network interface card (NIC), a modem, or a wireless transceiver. The communication unit 309 allows the electronic device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0077] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods described above, such as the control methods for a personal mobility robot. For example, in some embodiments, the control methods for a personal mobility robot can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed on an electronic device via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, the control methods for a personal mobility robot described above can be performed. Alternatively, in other embodiments, the computing unit 301 can be configured to perform the control methods for a personal mobility robot by any other suitable means (e.g., by means of firmware).

[0078] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this application, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0079] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0080] In the description of this application, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this application, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0081] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicating the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0082] Furthermore, the terms "first," "second," etc., used in the embodiments of this application are for descriptive purposes only and should not be construed as indicating or implying relative importance, or implicitly specifying the number of technical features indicated in this embodiment. Therefore, features defined with terms such as "first" and "second" in the embodiments of this application can explicitly or implicitly indicate that the embodiment includes at least one of those features. In the description of this application, the word "multiple" means at least two or more, such as two, three, four, etc., unless otherwise explicitly and specifically defined in the embodiments.

[0083] In this application, unless otherwise explicitly specified or limited in the embodiments, the terms "installation," "connection," "joining," and "fixing" appearing in the embodiments should be interpreted broadly. For example, a connection can be a fixed connection, a detachable connection, or an integral part; it can also be a mechanical connection, an electrical connection, etc. Of course, it can also be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication between two components, or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific implementation.

[0084] In this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0085] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A control method of a mobility robot, characterized by, The method includes: The controller operation amount of the mobility robot is obtained, and the target driving parameters corresponding to the controller operation amount are determined based on a preset nonlinear mapping relationship. The personal mobility robot is controlled based on the target driving parameters, and the actual driving parameters are obtained. The preset nonlinear mapping relationship is updated based on the difference between the actual driving parameters and the target driving parameters.

2. The control method for the personal mobility robot according to claim 1, characterized in that, The handle operation amount includes a first operation amount in a first direction, and the target driving parameter includes a target speed; determining the target driving parameter corresponding to the handle operation amount based on a preset nonlinear mapping relationship includes: Based on the different preset intervals in which the first operation quantity is located, the mapping relationship between the target speed or the change in the target speed and the first operation quantity is determined respectively.

3. The control method for the personal mobility robot according to claim 2, characterized in that, The step of determining the linear relationship between the target speed or the change in the target speed and the first operation amount based on different preset intervals in which the first operation amount is located includes: When the first operation amount is greater than the first preset value and less than or equal to the second preset value, it is determined that the change in the target speed increases linearly with the first operation amount. When the first operation amount is greater than the second preset value and less than or equal to the third preset value, it is determined that the target speed increases linearly with the first operation amount; When the first operation amount is greater than the third preset value and less than or equal to the fourth preset value, it is determined that the change in the target speed decreases linearly with the first operation amount. When the first operation amount is greater than the fourth preset value and less than or equal to the fifth preset value, the target speed is determined to be the maximum speed. When the first operation amount is less than the first preset value and greater than or equal to the sixth preset value, it is determined that the change in the target speed increases linearly with the first operation amount; When the first operation amount is less than the sixth preset value and greater than or equal to the seventh preset value, it is determined that the target speed decreases linearly with the first operation amount; When the first operation amount is less than the seventh preset value and greater than or equal to the eighth preset value, it is determined that the change in the target speed decreases linearly with the first operation amount.

4. The control method for the personal mobility robot according to claim 1, characterized in that, The handle operation amount includes a second operation amount in a second direction, the target driving parameter includes a target angular velocity, and the step of determining the target driving parameter corresponding to the handle operation amount based on a preset nonlinear mapping relationship includes: When the second operation amount is greater than the first preset value and less than or equal to the ninth preset value, the target angular velocity corresponding to the handle operation amount is determined based on the exponential mapping relationship, wherein the exponent base of the exponential mapping relationship is greater than an integer 1; When the second operation amount is greater than the ninth preset value and less than or equal to the tenth preset value, the target angular velocity corresponding to the handle operation amount is determined based on the logarithmic mapping relationship, wherein the logarithmic base of the logarithmic mapping relationship is greater than the integer 1.

5. The control method for the personal mobility robot according to claim 2, characterized in that, The control of the personal mobility robot based on the target driving parameters includes: The target speed is divided into low, medium, and high speed thresholds, and the mobility robot is controlled in segments.

6. The control method for the personal mobility robot according to claim 5, characterized in that, The segmented control of the personal mobility robot includes: When the target speed is greater than the low speed threshold and less than or equal to the middle speed threshold, the personal mobility robot is controlled to perform an acceleration operation and maintain it for a first preset time. When the target speed is greater than the speed threshold and less than or equal to the speed high threshold, the personal mobility robot is controlled to perform uniform acceleration and maintain it for a second preset time. When the target speed is greater than the high speed threshold, the personal mobility robot is controlled to perform a deceleration operation and maintain it for a third preset time.

7. The control method for the personal mobility robot according to claim 6, characterized in that, The actual driving parameters include the current speed; the difference between the actual driving parameters and the target driving parameters includes the speed deviation and the rate of change of the speed deviation between the current speed and the target speed. The step of updating the preset nonlinear mapping relationship based on the difference between the actual driving parameters and the target driving parameters includes: Based on the different preset intervals in which the speed deviation and the rate of change of the speed deviation are located, at least one of the low speed threshold, the medium speed threshold, the high speed threshold, the first preset time, the second preset time, and the third preset time is updated.

8. The control method for the personal mobility robot according to claim 7, characterized in that, The step of updating at least one of the following based on different preset intervals in which the speed deviation and the rate of change of the speed deviation lie: the low speed threshold, the medium speed threshold, the high speed threshold, the first preset time, the second preset time, and the third preset time; includes: When the speed deviation is greater than a first deviation threshold, and the rate of change of the speed deviation is greater than zero and less than a first rate of change threshold, the speed threshold is reduced, and / or the first preset time is increased; When the speed deviation approaches zero and the rate of change of the speed deviation approaches zero, increase the speed threshold, and / or increase the speed high threshold, and / or decrease the first preset time; When the speed deviation is less than zero and greater than the second deviation threshold, and the rate of change of the speed deviation is less than zero and greater than the second rate of change threshold, the first preset time is reduced. When the speed deviation is greater than zero and less than the third deviation threshold, and the rate of change of the speed deviation is less than the third rate of change threshold, the high speed threshold is reduced, and / or the third preset time is increased; When the speed deviation is less than the fourth deviation threshold and the rate of change of the speed deviation is less than the third rate of change threshold, the third preset time is reduced. Wherein, the first deviation threshold > the third deviation threshold > zero > the second deviation threshold > the fourth deviation threshold; the first rate of change threshold > zero > the second rate of change threshold > the third rate of change threshold.

9. The control method for the personal mobility robot according to claim 4, characterized in that, The control of the personal mobility robot based on the target driving parameters includes: When the target angular velocity is less than or equal to the angular velocity threshold, the mobility robot is accelerated according to an exponential mode, wherein the exponent base of the exponential mode is greater than an integer 1. When the target angular velocity is greater than the angular velocity threshold, the mobility robot is accelerated according to a logarithmic mode, wherein the logarithmic base of the logarithmic mode is greater than the integer 1.

10. The control method for the personal mobility robot according to claim 9, characterized in that, The actual driving parameters include the current angular velocity; the difference between the actual driving parameters and the target driving parameters includes the angular velocity deviation and the rate of change of the angular velocity deviation between the current angular velocity and the target angular velocity; updating the preset nonlinear mapping relationship based on the difference between the actual driving parameters and the target driving parameters includes: When the angular velocity deviation is greater than the fifth deviation threshold and the rate of change of the angular velocity deviation is greater than zero and less than the fourth rate of change threshold, and / or when the angular velocity deviation is less than zero and greater than the sixth deviation threshold and the rate of change of the angular velocity deviation is less than zero and greater than the fifth rate of change threshold, and / or when the angular velocity deviation is less than the seventh deviation threshold and the rate of change of the velocity deviation is less than the sixth rate of change threshold, the exponential parameter of the exponential mode is increased. When the angular velocity deviation approaches zero and the rate of change of the angular velocity deviation approaches zero, and / or when the angular velocity deviation is greater than zero and less than the eighth deviation threshold, and the rate of change of the velocity deviation is less than the sixth rate of change threshold, switch to the logarithmic mode; Wherein, the fifth deviation threshold > the eighth deviation threshold > zero > the sixth deviation threshold > the seventh deviation threshold; the fourth rate of change threshold > zero > the fifth rate of change threshold > the sixth rate of change threshold.

11. A control device for a personal mobility robot, characterized in that, The device includes: The determination module is used to acquire the handle operation amount of the mobility robot and determine the target driving parameters corresponding to the handle operation amount based on a preset nonlinear mapping relationship; The control module is used to control the mobility robot based on the target driving parameters and to acquire the actual driving parameters; The update module is used to update the preset nonlinear mapping relationship based on the difference between the actual driving parameters and the target driving parameters.

12. A personal mobility robot, characterized in that, The device includes a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement the steps of the control method for the personal mobility robot according to any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements the steps of the control method for the personal mobility robot according to any one of claims 1-10.

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