Robot control method, robot, and readable storage medium
By setting up a sensor array on the robot's contact surface to acquire pressure scalar data, analyzing pressure vector data, and determining the motion trajectory of the actuator, the problem that single-dimensional pressure values in existing robot control methods are insufficient to meet the precise control requirements of complex interactive scenarios is solved, thus achieving high-precision robot operation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- MOXIAN TECH DONGGUAN CO LTD
- Filing Date
- 2025-06-20
- Publication Date
- 2026-07-07
AI Technical Summary
Existing robot control methods rely on sensing pressure values in a single dimension to make decisions and execute actions, which is insufficient to meet the precise control requirements of complex interactive scenarios.
By setting a sensor array on the contact surface, pressure scalar data is acquired, and pressure vector data, including pressure trigger position and position change value, is analyzed. Based on the preset pressure information and the relationship between the movement position, the target movement trajectory of the actuator is determined, and the actuator is driven to move by the drive mechanism.
It enables precise analysis and control of pressure information in complex interactive scenarios, meeting the requirements for high-precision robot operation.
Smart Images
Figure CN120735004B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of robotics, and more particularly to a robot control method, a robot, and a computer-readable storage medium. Background Technology
[0002] In many human-computer interaction scenarios, higher demands are placed on the real-time performance, multidimensionality, and precision of pressure sensing and control. In applications such as rehabilitation robots and collaborative robotic arms, pressure sensors, as core sensing units, can detect pressure data from the contact surface in real time and transmit it to the drive mechanism via millisecond-level signals for adaptive adjustment, forming a closed loop of "perception-decision-execution" to achieve human-computer interaction. Existing robot control methods typically rely on sensing a single-dimensional pressure value for decision-making and execution, which is insufficient to meet the precise control requirements of complex interaction scenarios. Summary of the Invention
[0003] This application provides a robot control method, a robot, and a computer-readable storage medium, which solves the problem that existing robot control methods rely on sensing a single-dimensional pressure value to make decisions and execute, making it difficult to meet the precise control requirements of complex interactive scenarios.
[0004] In a first aspect, this application provides a robot control method, the robot including a drive mechanism, an actuator, and a sensor array, the sensor array being disposed on a contact surface to be pressure detected, the method comprising:
[0005] Acquire pressure scalar data of the pressure exerted on the contact surface when the sensor array is triggered;
[0006] Determine the pressure vector data corresponding to the contact surface based on the pressure scalar data;
[0007] The target motion trajectory corresponding to the actuator is determined based on the pressure vector data;
[0008] The drive mechanism is controlled to drive the actuator to move according to the target motion trajectory.
[0009] In some embodiments, the pressure scalar data includes pressure values collected by the sensor array at multiple consecutive sampling times on the contact surface, and the pressure vector data includes pressure trigger position and pressure position change value; determining the pressure vector data corresponding to the contact surface based on the pressure scalar data includes:
[0010] Based on the pressure values of the contact surface collected by the sensor array at multiple consecutive sampling times, the pressure trigger position of the contact surface at each sampling time is determined;
[0011] The pressure position change value is determined based on the pressure trigger position of the contact surface at each sampling time.
[0012] In some embodiments, determining the pressure trigger position of the contact surface at each sampling moment based on the pressure values collected by the sensor array at multiple consecutive sampling moments includes:
[0013] Based on the pressure value of the contact surface collected by the sensor array at each sampling time, the position of the pressure center of gravity in the sensor array corresponding to the pressure value at each sampling time is calculated.
[0014] The pressure trigger position of the contact surface at each sampling moment is determined based on the pressure value corresponding to the pressure center position in the sensor array.
[0015] In some embodiments, determining the pressure position change value based on the pressure trigger position of the contact surface at each sampling time includes:
[0016] The pressure position change value is determined sequentially based on the position difference between the pressure trigger positions at two adjacent sampling times.
[0017] In some embodiments, the pressure vector data includes pressure trigger positions and pressure position change values corresponding to multiple consecutive sampling times; determining the target motion trajectory corresponding to the actuator based on the pressure vector data includes:
[0018] Based on the preset correspondence between pressure information and movement position, the target movement position of the actuator at each sampling moment is determined according to the pressure trigger position and pressure position change value corresponding to multiple consecutive sampling moments;
[0019] Based on the target motion position of the actuator at each sampling time, the target motion trajectory corresponding to the actuator is generated.
[0020] In some embodiments, controlling the drive mechanism to drive the actuator to move according to the target motion trajectory includes:
[0021] The rotation information of the drive mechanism is calculated based on the target motion trajectory;
[0022] Based on a preset adaptive adjustment algorithm, the voltage value required by the drive mechanism is determined according to the rotation information;
[0023] The drive mechanism is controlled based on the voltage value to drive the actuator to move.
[0024] In some embodiments, the target motion trajectory includes the target motion position of the actuator; the step of controlling the drive mechanism to drive the actuator to move based on the voltage value further includes:
[0025] The current motion position of the actuator is determined based on the encoder in the actuator, and the current motion position is compared with the target motion position;
[0026] If the actuator is determined to move to the target position based on the current position, then the drive mechanism is controlled to stop driving the actuator to move.
[0027] In some embodiments, the sensor array includes pressure sensors distributed at multiple locations on the contact surface, wherein the pressure sensors are piezoresistive sensors.
[0028] Secondly, this application also provides a robot, which includes a processor, a memory, a drive mechanism, an actuator, and a sensor array;
[0029] The memory is used to store computer programs;
[0030] The drive mechanism is used to drive the actuator to move;
[0031] The sensor array is used to collect pressure scalar data of the pressure exerted on the contact surface when it is triggered;
[0032] The processor is configured to execute the computer program and, in executing the computer program, implement the robot control method as described above.
[0033] Thirdly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to implement the robot control method described above.
[0034] The aforementioned robot control method, robot, and computer-readable storage medium determine the pressure vector data corresponding to the contact surface based on pressure scalar data, determine the target motion trajectory of the actuator based on the pressure vector data, and control the drive mechanism to drive the actuator to move according to the target motion trajectory. This enables the generation of pressure vector data from pressure scalar data, the parsing of pressure trigger position and pressure position change value, and accurate driving of the actuator to move based on the pressure trigger position and pressure position change value. This solves the problem that existing robot control methods rely on sensing a single-dimensional pressure value to make decisions and execute, which is difficult to meet the precise control requirements of complex interactive scenarios. The control is more precise and can meet the precise control requirements of complex interactive scenarios. Attached Figure Description
[0035] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0036] Figure 1 This is a schematic diagram of the hardware structure of a robot provided in an embodiment of this application;
[0037] Figure 2 This is a schematic flowchart of a robot control method provided in an embodiment of this application;
[0038] Figure 3 This is a schematic diagram of a contact surface provided in an embodiment of this application;
[0039] Figure 4 This is a schematic diagram illustrating the relationship between a pressure triggering position and a target motion trajectory, provided in an embodiment of this application.
[0040] Figure 5 This is a schematic diagram illustrating a contact surface subjected to pressure, provided in an embodiment of this application.
[0041] Figure 6 This is a schematic diagram of a driving mechanism driving an actuator to move, provided in an embodiment of this application. Detailed Implementation
[0042] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0043] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.
[0044] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.
[0045] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.
[0046] With the rapid development of humanoid robots, adult toys, and virtual reality technology, many human-computer interaction scenarios have placed higher demands on the real-time performance, multidimensionality, and precision of pressure perception. In applications such as rehabilitation robots and collaborative robotic arms, pressure sensors, as core sensing units, can detect pressure data on the contact surface in real time and transmit it to the drive mechanism via millisecond-level signals to perform adaptive adjustments, forming a closed loop of "perception-decision-execution," thereby realizing human-computer interaction functions. In existing robot control methods, the perception dimension is singular and lacks directional analysis. For example, existing single-point piezoresistive sensors mainly rely on scalar detection, which can only capture the magnitude of pressure in a single dimension and cannot identify the direction of pressure. While capacitive sensors can detect pressure at multiple points, they are susceptible to environmental interference (such as electromagnetic fields and humidity), leading to signal distortion, and lack the ability to analyze the direction of pressure changes, making it difficult to support the precise control requirements of complex interaction scenarios.
[0047] To address this, embodiments of this application provide a robot control method, a robot, and a computer-readable storage medium. This method can generate pressure vector data based on pressure scalar data, analyze the pressure trigger position and pressure position change value, and then accurately drive the actuator to move based on the pressure trigger position and pressure position change value. This solves the problem that existing robot control methods rely on sensing a single-dimensional pressure value to make decisions and execute, which is insufficient to meet the precise control requirements of complex interactive scenarios. The control is more precise and can meet the precise control requirements of complex interactive scenarios.
[0048] For example, a robot can be a humanoid robot such as a rehabilitation robot or a collaborative robotic arm, or an electronic device such as an adult toy or a wearable device.
[0049] Please see Figure 1 , Figure 1 This is a schematic diagram of the hardware structure of a robot 100 provided in an embodiment of this application. The robot 100 may include a processor 1001, a memory 1002, a drive mechanism 1003, an actuator 1004, and a sensor array 1005. The processor 1001, memory 1002, drive mechanism 1003, actuator 1004, and sensor array 1005 can be connected via a bus, which can be any suitable bus such as an Inter-integrated Circuit (I2C) bus.
[0050] The memory 1002 may include a storage medium and internal memory. The storage medium may store an operating system and a computer program. The computer program includes program instructions, which, when executed, cause the processor 1001 to perform the robot control method corresponding to the robot 100 described in any embodiment.
[0051] The processor 1001 provides computing and control capabilities to support the operation of the entire robot 100.
[0052] The drive mechanism 1003 is connected to the actuator 1004 and is used to drive the actuator 1004 to move. The drive mechanism 1003 refers to the mechanism that provides power, and may include a motor, such as a servo motor or stepper motor, or a transmission device, such as a drive shaft or lead screw. The actuator 1004 refers to the mechanism that uses the power provided by the drive mechanism 1003 to perform corresponding actions (e.g., grasping, moving, sensing), such as a robotic arm, robotic hand, or wheels in a humanoid robot.
[0053] The sensor array 1005 can be disposed on the contact surface to collect pressure scalar data of the pressure exerted on the contact surface when it is triggered. The sensor array 1005 may include multiple pressure sensors.
[0054] The processor 1001 can be a Central Processing Unit (CPU), but it can also be a general-purpose processor, a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or it can be any conventional processor.
[0055] In one embodiment, the processor 1001 is configured to run a computer program stored in the memory 1002 to perform the following steps:
[0056] The sensor array acquires scalar pressure data of the pressure on the contact surface when it is triggered; the pressure vector data corresponding to the contact surface is determined based on the scalar pressure data; the target motion trajectory of the actuator is determined based on the pressure vector data; and the drive mechanism is controlled to drive the actuator to move according to the target motion trajectory.
[0057] In one embodiment, the pressure scalar data includes the pressure values experienced by the contact surface acquired by the sensor array at multiple consecutive sampling times, and the pressure vector data includes the pressure trigger position and the pressure position change value; the processor 1001, when determining the pressure vector data corresponding to the contact surface based on the pressure scalar data, is used to:
[0058] Based on the pressure values of the contact surface collected by the sensor array at multiple consecutive sampling times, the pressure trigger position of the contact surface at each sampling time is determined; based on the pressure trigger position of the contact surface at each sampling time, the pressure position change value is determined.
[0059] In one embodiment, when the processor 1001 determines the pressure trigger position of the contact surface at each sampling moment by acquiring pressure values of the contact surface based on the sensor array at multiple consecutive sampling moments, it is configured to:
[0060] Based on the pressure values collected by the sensor array at each sampling time on the contact surface, the pressure centroid position of the corresponding pressure value in the sensor array at each sampling time is calculated; based on the pressure centroid position of the corresponding pressure value in the sensor array at each sampling time, the pressure trigger position of the contact surface at each sampling time is determined.
[0061] In one embodiment, when the processor 1001 determines the pressure position change value based on the pressure trigger position of the contact surface at each sampling time, it is used to:
[0062] The pressure position change value is determined sequentially based on the position difference between the pressure trigger positions at two adjacent sampling times.
[0063] In one embodiment, the pressure vector data includes pressure trigger positions and pressure position change values corresponding to multiple consecutive sampling times; the processor 1001, when determining the target motion trajectory corresponding to the actuator based on the pressure vector data, is used to:
[0064] Based on the pre-defined correspondence between pressure information and movement position, the target movement position of the actuator at each sampling time is determined according to the pressure trigger position and pressure position change value corresponding to multiple consecutive sampling times; and the target movement trajectory of the actuator is generated according to the target movement position of the actuator at each sampling time.
[0065] In one embodiment, when the processor 1001 controls the drive mechanism to drive the actuator to move according to the target motion trajectory, it is used to implement:
[0066] The rotation information of the drive mechanism is calculated based on the target motion trajectory; the required voltage value of the drive mechanism is determined based on the rotation information using a preset adaptive adjustment algorithm; and the drive mechanism is controlled to drive the actuator to move based on the voltage value.
[0067] The following detailed description, in conjunction with the accompanying drawings, outlines some embodiments of this application. Unless otherwise specified, the following embodiments and features described herein can be combined with each other. Please refer to... Figure 2 , Figure 2 This is a schematic flowchart illustrating a robot control method provided in an embodiment of this application. Figure 2 As shown, the robot control method may include the following steps S101 to S104.
[0068] Step S101: Obtain pressure scalar data of the pressure on the contact surface when the sensor array is triggered.
[0069] For example, the robot can acquire pressure scalar data of the pressure exerted on the contact surface when the sensor array is triggered. The pressure scalar data includes the pressure values exerted on the contact surface at multiple consecutive sampling times. It is understood that the pressure scalar data may include pressure values, but not vector data such as the direction of pressure movement or positional changes.
[0070] For example, the contact surface can be one or more surfaces to be pressure detected, and can be set on the robot's actuator or at other locations on the robot; this application does not limit this.
[0071] In some embodiments, the sensor array includes pressure sensors distributed at multiple locations on the contact surface, wherein the pressure sensors are piezoresistive sensors.
[0072] It should be noted that, compared to capacitive sensors, piezoresistive sensors are sensors based on the piezoresistive effect. They can convert pressure changes into electrical signals and avoid environmental interference, such as accidental triggering due to water stains, and signal distortion caused by electromagnetic fields and humidity, thus greatly improving the accuracy of pressure detection. Furthermore, while existing single-point piezoresistive sensors mainly rely on scalar detection, this application, by setting pressure sensors at multiple points on the contact surface, can not only detect pressure values but also analyze the pressure trigger position and pressure position change value from the pressure values collected by the multiple pressure sensors, thereby meeting the precise control requirements of complex interactive scenarios.
[0073] Please see Figure 3 , Figure 3 This is a schematic diagram of a contact surface provided in an embodiment of this application. For example... Figure 3As shown, pressure sensors are distributed at five points on the contact surface. For example, one pressure sensor is installed at each of points 1, 2, 3, 4, and 5. The distribution of pressure sensors on the contact surface can be set according to the actual situation. For example, multiple pressure sensors can be distributed in multiple rows and columns on the contact surface. Of course, other distribution methods are also possible.
[0074] For example, such as Figure 3 As shown, the pressure values of the contact surface can be obtained from the pressure sensors corresponding to points 1, 2, 3, 4, and 5 at multiple consecutive sampling times, thus obtaining pressure scalar data.
[0075] Step S102: Determine the pressure vector data corresponding to the contact surface based on the pressure scalar data.
[0076] In this embodiment, after acquiring the pressure scalar data of the pressure experienced by the sensor array when the contact surface is triggered, pressure vector data can be parsed from the pressure scalar data. The following will provide a detailed explanation of how to parse the pressure vector data.
[0077] In some embodiments, the pressure vector data includes pressure trigger position and pressure position change value. Determining the pressure vector data corresponding to the contact surface based on the pressure scalar data may include: determining the pressure trigger position of the contact surface at each sampling time based on the pressure values of the contact surface collected by the sensor array at multiple consecutive sampling times; and determining the pressure position change value based on the pressure trigger position of the contact surface at each sampling time.
[0078] In some embodiments, determining the pressure trigger position of the contact surface at each sampling moment based on the pressure values collected by the sensor array at multiple consecutive sampling moments may include: calculating the pressure centroid position of the pressure value corresponding to each sampling moment in the sensor array based on the pressure values collected by the sensor array at each sampling moment; and determining the pressure trigger position of the contact surface at each sampling moment based on the pressure centroid position of the pressure value corresponding to each sampling moment in the sensor array.
[0079] For example, the formula for calculating the position of the pressure center of gravity is as follows:
[0080]
[0081] In the formula, Indicates the first in the sensor array Line number The column represents the pressure value collected by the pressure sensor, where M and N are the row and column numbers of the pressure sensors in the sensor array, respectively. This represents the coordinates of the pressure center of gravity within the sensor array. It should be noted that the x-coordinate of the pressure center of gravity... The denominator is the sum of the pressure values collected by each pressure sensor in the sensor array, and the x-axis is... The numerator is the sum of the product of the pressure values collected by each pressure sensor in the sensor array and the column number of each pressure sensor; the ordinate is... The numerator is the sum of the product of the pressure values collected by each pressure sensor in the sensor array and the row number of each pressure sensor.
[0082] For example, the above formula can be used to calculate the position of the pressure centroid in the sensor array corresponding to the pressure value at sampling time t. Position of pressure center The pressure trigger position on the contact surface at sampling time t is determined. It should be noted that, in this embodiment, the pressure centroid position can be used as the pressure trigger position.
[0083] In some embodiments, determining the pressure position change value based on the pressure trigger position of the contact surface at each sampling time includes: determining the pressure position change value sequentially based on the position difference between the pressure trigger positions of two adjacent sampling times.
[0084] For example, for sampling time t and sampling time (t-1), the pressure trigger position at sampling time t can be... Pressure trigger position at sampling time (t-1) Subtracting the two values yields the pressure position change value between sampling time t and sampling time (t-1).
[0085] Step S103: Determine the target motion trajectory corresponding to the actuator based on the pressure vector data.
[0086] In some embodiments, the pressure vector data includes pressure trigger positions and pressure position change values corresponding to multiple consecutive sampling times; determining the target motion trajectory corresponding to the actuator based on the pressure vector data may include: determining the target motion position of the actuator at each sampling time based on the preset correspondence between pressure information and motion position, according to the pressure trigger positions and pressure position change values corresponding to multiple consecutive sampling times; and generating the target motion trajectory corresponding to the actuator based on the target motion position of the actuator at each sampling time.
[0087] It should be noted that, in this embodiment, a pressure information-motion position mapping model can be pre-constructed. The pressure information can include the pressure trigger position and the pressure position change value. The pressure information-motion position mapping model can include the correspondence between the pressure trigger position, the pressure position change value, and the motion position. Here, the motion position refers to the displacement required by the actuator when the trigger position of the pressure on the contact surface and the magnitude of the trigger position change.
[0088] For example, the pressure trigger position and pressure position change value corresponding to multiple consecutive sampling times can be input into the pressure information-motion position mapping model to calculate the target motion position of the actuator at each sampling time. Then, by connecting the target motion positions of the actuator at each sampling time, the target motion trajectory of the actuator can be obtained.
[0089] It should be noted that, in the embodiments of this application, by using a pressure information-motion position mapping model to nonlinearly couple pressure information with the motion position of the actuator, adaptive adjustment under dynamic load can be achieved, resulting in more precise control and thus meeting the precise control requirements of complex interactive scenarios.
[0090] Please see Figure 4 , Figure 4 This is a schematic diagram illustrating the relationship between a pressure trigger position and the target motion trajectory of an actuator, as provided in an embodiment of this application. Figure 4 As shown, curve 1 represents the pressure trigger position, and curve 2 represents the target motion trajectory. The target motion trajectory of the actuator changes with the change of the pressure trigger position. The actuator can accurately reproduce the human body's operating intention and realize millisecond-level closed-loop human-computer interaction from tactile perception to action feedback.
[0091] Step S104: Control the drive mechanism to drive the actuator to move according to the target motion trajectory.
[0092] In some embodiments, controlling the drive mechanism to drive the actuator to move according to the target motion trajectory may include: calculating the rotation information of the drive mechanism according to the target motion trajectory; determining the voltage value required by the drive mechanism based on the rotation information according to a preset adaptive adjustment algorithm; and controlling the drive mechanism to drive the actuator to move based on the voltage value.
[0093] For example, the target motion trajectory may include the target motion position that the actuator needs to move to, and the rotation information may include the number of rotations of the motor. For instance, when the target motion position is position A, the number of rotations required for the motor to drive the actuator to move to position A can be calculated based on position A and the radius of the motor rotor.
[0094] For example, the preset adaptive adjustment algorithm may include a PID (proportional, integral, derivative) adjustment algorithm. For instance, the required voltage value for the drive mechanism can be calculated based on the number of rotations of the drive mechanism using a PID adjustment algorithm. The specific voltage calculation process can be found in related technologies, and will not be elaborated upon here.
[0095] By using a PID control algorithm to determine the voltage value based on rotation information, the synergistic effect of the proportional (P), integral (I), and derivative (D) components can be utilized to achieve precise control of the voltage value required by the drive mechanism.
[0096] For example, after determining the voltage value required by the drive mechanism, the drive mechanism can be controlled to drive the actuator to move based on the voltage value.
[0097] In some embodiments, controlling the drive mechanism to drive the actuator to move based on the voltage value may further include: determining the current movement position of the actuator based on the encoder in the actuator, and comparing the current movement position with the target movement position; if it is determined that the actuator has moved to the target movement position based on the current movement position, then controlling the drive mechanism to stop driving the actuator to move.
[0098] For example, during the process of driving the actuator to move based on voltage value control, the current position of the actuator can be detected in real time by the encoder in the actuator, and compared with the target position. For instance, when the target position is position A, the current position of the actuator can be compared with position A to determine whether the actuator has moved to position A. If it is determined that the actuator has moved to position A, the drive mechanism is controlled to stop driving the actuator to move. If it is determined that the actuator has not moved to position A, the drive mechanism is controlled to continue driving the actuator to move until the actuator moves to position A.
[0099] Please see Figure 5 and Figure 6 , Figure 5 This is a schematic diagram illustrating pressure applied to a contact surface according to an embodiment of this application. Figure 6 This is a schematic diagram of a driving mechanism driving an actuator to move, provided in an embodiment of this application.
[0100] Combination Figure 5 and Figure 6When user pressure triggers point 1 on the contact surface, the pressure sensor corresponding to point 1 detects the pressure value. At this time, the pressure center of gravity is located at point 1, and the actuator is in the initial position. When sliding from point 1 to point 3, the pressure value detected by the pressure sensor at point 1 gradually decreases, the pressure moves to point 2, and the pressure center of gravity moves towards point 2. The drive mechanism drives the actuator to move to the right accordingly. When moving from point 2 to point 3, the pressure detected by the pressure sensor at point 2 decreases, and the pressure detected by the pressure sensor at point 3 increases. The pressure center of gravity moves from point 2 to point 3, and the actuator moves from the position corresponding to point 2 to the position corresponding to point 3. This continues until the pressure completely triggers point 3, at which point the pressure center of gravity is located at point 3, and the actuator stops at the final position.
[0101] The robot control method provided in the above embodiments determines the pressure vector data corresponding to the contact surface based on pressure scalar data, determines the target motion trajectory of the actuator based on the pressure vector data, and controls the drive mechanism to drive the actuator to move according to the target motion trajectory. It can generate pressure vector data based on pressure scalar data, and can analyze the pressure trigger position and pressure position change value. Then, it can accurately drive the actuator to move according to the pressure trigger position and pressure position change value. This solves the problem that existing robot control methods rely on sensing a single-dimensional pressure value to make decisions and execute, which is difficult to meet the precise control requirements of complex interactive scenarios. The control is more precise and can meet the precise control requirements of complex interactive scenarios.
[0102] The embodiments of this application also provide a computer-readable storage medium storing a computer program, which includes program instructions. The processor executes the program instructions to implement any of the robot control methods provided in the embodiments of this application.
[0103] For example, when the program is loaded by the processor, it can perform the following steps:
[0104] The sensor array acquires scalar pressure data of the pressure on the contact surface when it is triggered; the pressure vector data corresponding to the contact surface is determined based on the scalar pressure data; the target motion trajectory of the actuator is determined based on the pressure vector data; and the drive mechanism is controlled to drive the actuator to move according to the target motion trajectory.
[0105] The computer-readable storage medium can be an internal storage unit of the robot in the aforementioned embodiments, such as the robot's hard drive or memory. Alternatively, it can be an external storage device for the robot, such as a plug-in hard drive, a smart media card (SMC), a secure digital card (SD card), or a flash card.
[0106] Furthermore, the computer-readable storage medium may primarily include a stored program area and a stored data area, wherein the stored program area may store the operating system, an application program required for at least one function, etc.; and the stored data area may store data created based on the use of blockchain nodes, etc.
[0107] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
Claims
1. A robot control method, characterized in that, The robot includes a drive mechanism, an actuator, and a sensor array, wherein the sensor array is disposed on the contact surface to be pressure detected, and the method includes: Acquire pressure scalar data of the pressure exerted on the contact surface when the sensor array is triggered; Determine the pressure vector data corresponding to the contact surface based on the pressure scalar data; The target motion trajectory corresponding to the actuator is determined based on the pressure vector data; The drive mechanism is controlled to drive the actuator to move according to the target motion trajectory; The pressure scalar data includes the pressure values that the sensor array collects at multiple consecutive sampling times on the contact surface, and the pressure vector data includes the pressure trigger position and the pressure position change value; Determining the pressure vector data corresponding to the contact surface based on the pressure scalar data includes: Based on the pressure values of the contact surface collected by the sensor array at multiple consecutive sampling times, the pressure trigger position of the contact surface at each sampling time is determined; based on the pressure trigger position of the contact surface at each sampling time, the pressure position change value is determined. The step of determining the pressure trigger position of the contact surface at each sampling moment by collecting pressure values of the contact surface at multiple consecutive sampling moments using the sensor array includes: Based on the pressure value of the contact surface collected by the sensor array at each sampling time, the pressure center position of the pressure value corresponding to each sampling time in the sensor array is calculated; based on the pressure center position of the pressure value corresponding to each sampling time in the sensor array, the pressure trigger position of the contact surface at each sampling time is determined.
2. The robot control method according to claim 1, characterized in that, The step of determining the pressure position change value based on the pressure trigger position of the contact surface at each sampling time includes: The pressure position change value is determined sequentially based on the position difference between the pressure trigger positions at two adjacent sampling times.
3. The robot control method according to claim 1, characterized in that, The pressure vector data includes pressure trigger positions and pressure position change values corresponding to multiple consecutive sampling times; determining the target motion trajectory corresponding to the actuator based on the pressure vector data includes: Based on the preset correspondence between pressure information and movement position, the target movement position of the actuator at each sampling moment is determined according to the pressure trigger position and pressure position change value corresponding to multiple consecutive sampling moments; Based on the target motion position of the actuator at each sampling time, the target motion trajectory corresponding to the actuator is generated.
4. The robot control method according to claim 1, characterized in that, The step of controlling the drive mechanism to drive the actuator to move according to the target motion trajectory includes: The rotation information of the drive mechanism is calculated based on the target motion trajectory; Based on a preset adaptive adjustment algorithm, the voltage value required by the drive mechanism is determined according to the rotation information; The drive mechanism is controlled based on the voltage value to drive the actuator to move.
5. The robot control method according to claim 4, characterized in that, The target motion trajectory includes the target motion position of the actuator; the step of controlling the drive mechanism to drive the actuator to move based on the voltage value further includes: The current motion position of the actuator is determined based on the encoder in the actuator, and the current motion position is compared with the target motion position; If the actuator is determined to move to the target position based on the current position, then the drive mechanism is controlled to stop driving the actuator to move.
6. The robot control method according to any one of claims 1-5, characterized in that, The sensor array includes pressure sensors distributed at multiple locations on the contact surface, and the pressure sensors are piezoresistive sensors.
7. A robot, characterized in that, The robot includes a processor, memory, drive mechanism, actuator, and sensor array; The memory is used to store computer programs; The drive mechanism is used to drive the actuator to move; The sensor array is used to collect pressure scalar data of the pressure exerted on the contact surface when it is triggered; The processor is configured to execute the computer program and, in executing the computer program, implement the robot control method as described in any one of claims 1 to 6.
8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to implement the robot control method as described in any one of claims 1 to 6.