Method for controlling robot through intelligent terminal

Abstract

The invention relates to the field of artificial intelligence, and discloses a method for controlling a robot through an intelligent terminal, which comprises the following steps: S01, the intelligent terminal sends a control signal and generates an expected track, S02, the robot receives the control signal and generates a motion track, and S03, track compensation analysis is carried out on the robot according to the expected track and the motion track, and the robot is controlled through the intelligent terminal. S04, establishing a double-track coupling analysis model based on the expected track and the motion track, S05, calculating a track deviation compensation index by the intelligent terminal according to a track coupling coefficient, S06, completing intelligent control of the robot from the robot position to the target position, receiving a control signal by the robot and judging whether the generated expected track contains an obstacle or not, and if yes, executing the step S05; and the motion track is generated according to the judgment result, deviation compensation is performed on the robot motion track feature points to adjust the motion track, and the control precision and efficiency of the robot are improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence, and more specifically to a method for controlling a robot through an intelligent terminal. Background Art

[0002] An intelligent robot is a comprehensive system that integrates multiple functions such as environmental perception, dynamic decision-making and planning, behavior control and execution. It integrates advanced technologies from multiple disciplines such as computer science, informatics, mechanical motion and dynamics, and control theory. It is one of the frontier areas of scientific and technological development. Traditional intelligent robots are mainly industrial robots, and the control method is mainly simple teaching and reproduction. Robots can only perform repetitive actions according to pre-set trajectories. With the development of computer technology and artificial intelligence, robot control technology has begun to introduce perception devices such as sensors and vision systems, and has developed model-based control methods, allowing robots to adapt to more complex environments and tasks. Intelligent robots have the capabilities of perception, recognition, understanding, decision-making, and execution. They can autonomously perceive the external environment, understand human instructions, and respond accordingly.

[0003] In existing robot control technology, it is usually necessary to use complex programming and operating interfaces to achieve precise control of the robot. This method is not only time-consuming, but also requires high professional skills from the operator. In addition, when the robot encounters unknown obstacles or environmental changes while performing tasks, traditional control methods are often difficult to adapt quickly, resulting in low task execution efficiency. Current robot control technology still has deficiencies in vision, hearing, touch and other perceptions, and it is difficult to reach the level of human perception. This may cause errors in the robot's understanding of the environment and human instructions, and the lack of an adjustment mechanism means that errors cannot be discovered and processed in a timely manner. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a method for controlling a robot through an intelligent terminal to solve the problems existing in the above-mentioned background technology.

[0005] The present invention provides the following technical solution: a method for controlling a robot through an intelligent terminal, comprising the following steps: Step S01: the intelligent terminal sends a control signal and generates a desired trajectory: the intelligent terminal uses wireless communication technology to send a control signal to the robot, and generates a desired trajectory based on the robot position and the target position; Step S02: The robot receives the control signal and generates a motion trajectory: The robot receives the control signal and determines whether the generated desired trajectory contains obstacles, generates a motion trajectory based on the determination result, and executes the motion instruction; Step S03: performing trajectory compensation analysis on the robot according to the expected trajectory and the motion trajectory: extracting feature points of the expected trajectory and the motion trajectory, performing trajectory compensation analysis on the feature points, and the intelligent terminal determines whether to send a trajectory compensation instruction; Step S04: establishing a dual-track coupling analysis model based on the expected track and the motion track: receiving a track compensation instruction sent by the intelligent terminal, establishing a dual-track coupling analysis model based on the expected track and the motion track to calculate the track coupling coefficient; Step S05: the intelligent terminal calculates the trajectory deviation compensation index according to the trajectory coupling coefficient: the intelligent terminal establishes a trajectory deviation compensation model based on the trajectory coupling coefficient to calculate the trajectory deviation compensation index, and performs deviation compensation on the characteristic points of the robot's motion trajectory according to the trajectory deviation compensation index to adjust the motion trajectory; Step S06: Complete intelligent control of the robot from the robot position to the target position: During the process of the robot executing the motion instructions, the intelligent terminal monitors the motion state of the robot in real time to complete the intelligent control of the robot.

[0006] Preferably, in step S01, the intelligent terminal collects the motion parameters of the robot in real time through built-in sensors, and transmits the parameters to the control center through wireless communication technology. The control center sends a control signal to the robot, and the intelligent terminal inputs or selects the target position through the user interface, and calibrates the target position and the robot position at the same time.

[0007] Preferably, in step S02, the robot receives the control signal and the generated expected trajectory, and determines through the camera whether the generated expected trajectory contains an obstacle. If it is determined that there is an obstacle, the judgment result and the obstacle information are sent to step S01 to regenerate the expected trajectory. If it is determined that there is no obstacle, a motion trajectory is generated.

[0008] Preferably, in step S03, the specific contents of performing trajectory compensation analysis on the robot according to the expected trajectory and the motion trajectory are as follows: Extract the coordinates of the feature points of the desired trajectory , i represents the feature point number of the expected trajectory, i=1, 2, 3, ..., n, n represents the total number of feature points of the expected trajectory, and the feature point represents the inflection point in the curve formed by the expected trajectory. If the expected trajectory is a straight line, the feature point is the midpoint of the straight line; Extract the coordinates of the feature points of the motion trajectory corresponding to the feature points of the desired trajectory , calculate the distance between the feature points of each expected trajectory and the feature points of the motion trajectory, and the calculation formula is: ,in Indicates the distance between the feature points of each expected trajectory and the feature points of the motion trajectory; Combined with the time data characteristics, the trajectory compensation analysis is performed on the characteristic points of the motion trajectory. The calculation formula is: ,in Represents the output value of trajectory compensation analysis for the feature points of the motion trajectory. It represents the time it takes for the robot to reach each feature point of the desired trajectory from the robot position. It represents the time it takes for the robot to reach each characteristic point of the motion trajectory from the robot position; The output value of the trajectory compensation analysis Compared with the preset compensation threshold, if the output value of the trajectory compensation analysis is greater than or equal to the preset compensation threshold, the intelligent terminal determines to send a trajectory compensation instruction; if the output value of the trajectory compensation analysis is less than the preset compensation threshold, the intelligent terminal determines not to send a trajectory compensation instruction.

[0009] Preferably, in step S04, the specific contents of establishing the dual-track coupling analysis model based on the expected track and the motion track are as follows: Receive the trajectory compensation command sent by the intelligent terminal, and establish a dual-trajectory coupling analysis model to calculate the trajectory coupling coefficient based on the desired trajectory and the direction deflection coefficient of each feature point of the motion trajectory. The calculation formula is: ; Said represents the trajectory coupling coefficient, It represents the active force coefficient of the robot from the i-th feature point to the i+1-th feature point in the motion trajectory. represents the active force coefficient of the robot from the i-th feature point to the i+1-th feature point in the expected trajectory, Indicates the direction deflection coefficient of the robot from the i-th feature point to the i+1-th feature point in the motion trajectory, Represents the directional deflection coefficient of the robot from the i-th feature point to the i+1-th feature point in the expected trajectory.

[0010] Preferably, the specific calculation contents of the direction deflection coefficients of the desired trajectory and each characteristic point of the motion trajectory are as follows: Calculate the length between the i-th feature point and the i+1-th feature point in the motion trajectory. The calculation formula is: ,in Indicates the length between the i-th feature point and the i+1-th feature point in the motion trajectory; The directional deflection coefficient of each feature point in the motion trajectory is calculated based on the length between the feature points. The calculation formula is: ,in Represents the direction deflection coefficient of each feature point in the motion trajectory, Indicates the deflection angle from the i-th feature point to the i+1-th feature point in the motion trajectory; The direction deflection coefficient of each feature point in the expected trajectory is calculated based on the length between the feature points. The calculation formula is: ,in Represents the direction deflection coefficient of each feature point in the expected trajectory, represents the deflection angle from the i-th feature point to the i+1-th feature point in the expected trajectory, It represents the length between the i-th feature point and the i+1-th feature point in the expected trajectory.

[0011] Preferably, in step S05, the specific content of calculating the trajectory deviation compensation index according to the trajectory coupling coefficient by the intelligent terminal is as follows: Indicates the deflection angle from the i-th feature point to the i+1-th feature point in the motion trajectory. represents the deflection angle from the i-th feature point to the i+1-th feature point in the expected trajectory, where i=1, 2, 3, ..., n-1; The angle deviation compensation index between the motion trajectory and the expected trajectory is calculated based on the trajectory coupling coefficient. The calculation formula is: ,in It represents the angle deviation compensation index between the motion trajectory and the expected trajectory, and e represents a constant; Substitute the angle deviation compensation index into the trajectory deviation compensation model to calculate the trajectory deviation compensation index. The calculation formula is: ,in Indicates the trajectory deviation compensation index; The intelligent terminal controls the motion trajectory of the robot through the trajectory deviation compensation index. If the trajectory deviation compensation index of the robot's motion trajectory exceeds the preset threshold range, the feature point coordinates of the robot are adjusted until the trajectory deviation compensation index of the robot's motion trajectory is within the preset threshold range.

[0012] Preferably, in step S06, the intelligent terminal monitors the motion state of the robot in real time while the robot is executing motion instructions. The control center compares and analyzes the received real-time data with the preset motion trajectory and adjusts the control instructions in real time. Once an abnormal motion state of the robot is detected, an alarm will be immediately issued and measures will be taken to complete the intelligent control of the robot.

[0013] Technical effects and advantages of the present invention: The present invention is provided with step S01: the intelligent terminal sends a control signal and generates a desired trajectory, step S02: the robot receives the control signal and generates a motion trajectory, step S03: the robot is subjected to trajectory compensation analysis according to the desired trajectory and the motion trajectory, step S04: a dual-trajectory coupling analysis model is established based on the desired trajectory and the motion trajectory, step S05: the intelligent terminal calculates a trajectory deviation compensation index according to a trajectory coupling coefficient, and step S06: the robot is intelligently controlled from a robot position to a target position, thereby improving the control accuracy and efficiency of the robot; The robot receives control signals and determines whether the generated expected trajectory contains obstacles, generates a motion trajectory based on the judgment result, monitors the robot's motion state in real time through the intelligent terminal, and compares and analyzes it with the preset motion trajectory, ensuring the safety and reliability of the robot in the process of executing tasks, effectively avoiding the problem of low task execution efficiency caused by environmental changes, and adjusting the motion trajectory by compensating for deviations of the characteristic points of the robot's motion trajectory, achieving rapid adaptation and response to complex environments, and significantly improving the robot's flexibility and autonomy in performing tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The figure is a flowchart of a method for controlling a robot through an intelligent terminal. DETAILED DESCRIPTION

[0015] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are merely illustrative. The method of controlling a robot through an intelligent terminal involved in the present invention is not limited to the various structures recorded in the following embodiments. All other implementations obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0016] like Figure 1 As shown, the present invention provides a method for controlling a robot through an intelligent terminal, comprising the following steps: Step S01: the intelligent terminal sends a control signal and generates a desired trajectory: the intelligent terminal uses wireless communication technology to send a control signal to the robot, and generates a desired trajectory based on the robot position and the target position. The desired trajectory is a trajectory formed by the ideal path planned by the intelligent terminal for the robot according to the robot position and the target position; Step S02: The robot receives the control signal and generates a motion trajectory: The robot receives the control signal and determines whether the generated desired trajectory contains obstacles, generates a motion trajectory according to the determination result, and executes the motion command. The motion trajectory is a trajectory formed after dynamically adjusting the desired trajectory according to the robot's data feedback and environmental feedback; Step S03: performing trajectory compensation analysis on the robot according to the expected trajectory and the motion trajectory: extracting feature points of the expected trajectory and the motion trajectory, performing trajectory compensation analysis on the feature points, and the intelligent terminal determines whether to send a trajectory compensation instruction; Step S04: establishing a dual-track coupling analysis model based on the expected track and the motion track: receiving a track compensation instruction sent by the intelligent terminal, establishing a dual-track coupling analysis model based on the expected track and the motion track to calculate the track coupling coefficient; Step S05: the intelligent terminal calculates the trajectory deviation compensation index according to the trajectory coupling coefficient: the intelligent terminal establishes a trajectory deviation compensation model based on the trajectory coupling coefficient to calculate the trajectory deviation compensation index, and performs deviation compensation on the characteristic points of the robot's motion trajectory according to the trajectory deviation compensation index to adjust the motion trajectory; Step S06: Complete intelligent control of the robot from the robot position to the target position: During the process of the robot executing the motion instructions, the intelligent terminal monitors the motion state of the robot in real time to complete the intelligent control of the robot.

[0017] In this embodiment, it should be specifically explained that in step S01, the intelligent terminal collects the motion parameters of the robot in real time through the built-in sensors, and transmits the parameters to the control center through wireless communication technology. The control center sends a control signal to the robot, and the intelligent terminal inputs or selects the target position through the user interface, and calibrates the target position and the robot position at the same time.

[0018] In this embodiment, it should be specifically explained that in step S02, the robot receives the control signal and the generated desired trajectory, and determines whether the generated desired trajectory contains an obstacle through the camera. If it is determined that there is an obstacle, the determination result and the obstacle information are sent to step S01 to regenerate the desired trajectory. If it is determined that there is no obstacle, a motion trajectory is generated; The expected trajectory is the trajectory formed by the ideal path planned for the robot by the intelligent terminal according to the robot position and the target position, and the motion trajectory is the trajectory formed after the expected trajectory is dynamically adjusted according to the robot's data feedback and environmental feedback; After generating the motion trajectory, the robot uses its onboard cameras and sensors to monitor the environment in real time to ensure the accuracy and safety of the motion trajectory. If obstacles or potential dangers are detected during the movement, the robot will send the current status and environmental information back to the smart terminal through wireless communication technology. After receiving this information, the smart terminal will quickly analyze and re-plan the motion trajectory to avoid obstacles or dangerous areas, ensuring that the robot can continue to perform its tasks safely.

[0019] In this embodiment, it should be specifically explained that in step S03, the specific content of performing trajectory compensation analysis on the robot according to the expected trajectory and the motion trajectory is as follows: Extract the coordinates of the feature points of the desired trajectory , i represents the feature point number of the expected trajectory, i=1, 2, 3, ..., n, n represents the total number of feature points of the expected trajectory, and the feature point represents the inflection point in the curve formed by the expected trajectory. If the expected trajectory is a straight line, the feature point is the midpoint of the straight line, and n=1; Extract the coordinates of the feature points of the motion trajectory corresponding to the feature points of the desired trajectory , calculate the distance between the feature points of each expected trajectory and the feature points of the motion trajectory, and the calculation formula is: ,in Represents the distance between the feature points of each expected trajectory and the feature points of the motion trajectory, where Indicates the coordinates of the feature points of the desired trajectory. Indicates extracting the coordinates of the feature points of the motion trajectory corresponding to the feature points of the expected trajectory; Combined with the time data characteristics, the trajectory compensation analysis is performed on the characteristic points of the motion trajectory. The calculation formula is: ,in Represents the output value of trajectory compensation analysis for the feature points of the motion trajectory. It represents the time it takes for the robot to reach each feature point of the desired trajectory from the robot position. It represents the time it takes for the robot to reach each feature point of the motion trajectory from the robot position. represents the distance between the feature points of each expected trajectory and the feature points of the motion trajectory, and n represents the total number of feature points of the expected trajectory; The output value of the trajectory compensation analysis Compared with the preset compensation threshold, if the output value of the trajectory compensation analysis is greater than or equal to the preset compensation threshold, the intelligent terminal determines to send a trajectory compensation instruction; if the output value of the trajectory compensation analysis is less than the preset compensation threshold, the intelligent terminal determines not to send a trajectory compensation instruction.

[0020] In this embodiment, it should be specifically explained that in step S04, the specific content of establishing the dual-track coupling analysis model based on the expected track and the motion track is as follows: Receive the trajectory compensation command sent by the intelligent terminal, and establish a dual-trajectory coupling analysis model to calculate the trajectory coupling coefficient based on the desired trajectory and the direction deflection coefficient of each feature point of the motion trajectory. The calculation formula is: , where i=1, 2, 3, ..., n-1; Said represents the trajectory coupling coefficient, It represents the active force coefficient of the robot from the i-th feature point to the i+1-th feature point in the motion trajectory. represents the active force coefficient of the robot from the i-th feature point to the i+1-th feature point in the expected trajectory, Indicates the direction deflection coefficient of the robot from the i-th feature point to the i+1-th feature point in the motion trajectory, It represents the directional deflection coefficient of the robot from the i-th feature point to the i+1-th feature point in the expected trajectory. When the expected trajectory or motion trajectory is a straight line, i represents the starting point of the trajectory and i+1 represents the end point of the trajectory.

[0021] In this embodiment, it should be specifically explained that the specific calculation contents of the direction deflection coefficients of the desired trajectory and each feature point of the motion trajectory are as follows: Calculate the length between the i-th feature point and the i+1-th feature point in the motion trajectory. The calculation formula is: ,in Indicates the length between the i-th feature point and the i+1-th feature point in the motion trajectory. It means extracting the coordinates of the i-th motion trajectory feature point corresponding to the feature point of the expected trajectory. Indicates extracting the coordinates of the i+1th motion trajectory feature point corresponding to the feature point of the expected trajectory; The directional deflection coefficient of each feature point in the motion trajectory is calculated based on the length between the feature points. The calculation formula is: ,in Represents the direction deflection coefficient of each feature point in the motion trajectory, Indicates the deflection angle from the i-th feature point to the i+1-th feature point in the motion trajectory. Indicates the length between the i-th feature point and the i+1-th feature point in the motion trajectory; Calculate the length between the i-th feature point and the i+1-th feature point in the expected trajectory. The calculation formula is: ,in Indicates the length between the i-th feature point and the i+1-th feature point in the expected trajectory. Indicates the coordinates of the i-th feature point of the desired trajectory. Indicates the coordinates of the i+1th feature point of the desired trajectory; The direction deflection coefficient of each feature point in the expected trajectory is calculated based on the length between the feature points. The calculation formula is: ,in Represents the direction deflection coefficient of each feature point in the expected trajectory, represents the deflection angle from the i-th feature point to the i+1-th feature point in the expected trajectory, It represents the length between the i-th feature point and the i+1-th feature point in the expected trajectory.

[0022] In this embodiment, it should be specifically explained that in step S05, the specific content of calculating the trajectory deviation compensation index according to the trajectory coupling coefficient by the intelligent terminal is as follows: Indicates the deflection angle from the i-th feature point to the i+1-th feature point in the motion trajectory. represents the deflection angle from the i-th feature point to the i+1-th feature point in the expected trajectory, where i=1, 2, 3, ..., n-1; The angle deviation compensation index between the motion trajectory and the expected trajectory is calculated based on the trajectory coupling coefficient. The calculation formula is: ,in It represents the angle deviation compensation index between the motion trajectory and the expected trajectory, e represents a constant, Indicates the deflection angle from the i-th feature point to the i+1-th feature point in the motion trajectory. Indicates the deflection angle from the i-th feature point to the i+1-th feature point in the expected trajectory; Substitute the angle deviation compensation index into the trajectory deviation compensation model to calculate the trajectory deviation compensation index. The calculation formula is: ,in represents the trajectory deviation compensation index, Indicates the deflection angle from the i-th feature point to the i+1-th feature point in the motion trajectory. represents the deflection angle from the i-th feature point to the i+1-th feature point in the expected trajectory, Indicates the angle deviation compensation index between the motion trajectory and the expected trajectory; The intelligent terminal controls the motion trajectory of the robot through the trajectory deviation compensation index. If the trajectory deviation compensation index of the robot's motion trajectory exceeds the preset threshold range, the feature point coordinates of the robot are adjusted until the trajectory deviation compensation index of the robot's motion trajectory is within the preset threshold range.

[0023] In this embodiment, it should be specifically explained that in step S06, the intelligent terminal monitors the motion state of the robot in real time while the robot is executing motion instructions. The control center compares and analyzes the received real-time data with the preset motion trajectory and adjusts the control instructions in real time. Once an abnormal motion state of the robot is detected, an alarm will be immediately issued and measures will be taken to complete the intelligent control of the robot.

[0024] The difference between this embodiment and the prior art is that this embodiment is provided with step S01: the intelligent terminal sends a control signal and generates a desired trajectory, step S02: the robot receives the control signal and generates a motion trajectory, step S03: the robot is subjected to trajectory compensation analysis according to the desired trajectory and the motion trajectory, step S04: a dual-trajectory coupling analysis model is established based on the desired trajectory and the motion trajectory, step S05: the intelligent terminal calculates the trajectory deviation compensation index according to the trajectory coupling coefficient, and step S06: the robot is intelligently controlled from the robot position to the target position, thereby improving the control accuracy and efficiency of the robot; The robot receives control signals and determines whether the generated expected trajectory contains obstacles, generates a motion trajectory based on the judgment result, monitors the robot's motion state in real time through the intelligent terminal, and compares and analyzes it with the preset motion trajectory, ensuring the safety and reliability of the robot in the process of executing tasks, effectively avoiding the problem of low task execution efficiency caused by environmental changes, and adjusting the motion trajectory by compensating for deviations of the characteristic points of the robot's motion trajectory, achieving rapid adaptation and response to complex environments, and significantly improving the robot's flexibility and autonomy in performing tasks.

[0025] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0026] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for controlling a robot through an intelligent terminal, characterized in that: The following steps are involved: Step S01: the intelligent terminal sends a control signal and generates a desired trajectory: the intelligent terminal uses wireless communication technology to send a control signal to the robot, and generates a desired trajectory based on the robot position and the target position; Step S02: The robot receives the control signal and generates a motion trajectory: The robot receives the control signal and determines whether the generated desired trajectory contains obstacles, generates a motion trajectory based on the determination result, and executes the motion instruction; Step S03: performing trajectory compensation analysis on the robot according to the expected trajectory and the motion trajectory: extracting feature points of the expected trajectory and the motion trajectory, performing trajectory compensation analysis on the feature points, and the intelligent terminal determines whether to send a trajectory compensation instruction; Step S04: establishing a dual-track coupling analysis model based on the expected track and the motion track: receiving a track compensation instruction sent by the intelligent terminal, establishing a dual-track coupling analysis model based on the expected track and the motion track to calculate the track coupling coefficient; Step S05: the intelligent terminal calculates the trajectory deviation compensation index according to the trajectory coupling coefficient: the intelligent terminal establishes a trajectory deviation compensation model based on the trajectory coupling coefficient to calculate the trajectory deviation compensation index, and performs deviation compensation on the characteristic points of the robot's motion trajectory according to the trajectory deviation compensation index to adjust the motion trajectory; Step S06: Complete intelligent control of the robot from the robot position to the target position: During the process of the robot executing the motion instructions, the intelligent terminal monitors the motion state of the robot in real time to complete the intelligent control of the robot.

2. A method for controlling a robot through an intelligent terminal according to claim 1, characterized in that: In step S01, the intelligent terminal collects the motion parameters of the robot in real time through the built-in sensors, and transmits the parameters to the control center through wireless communication technology. The control center sends a control signal to the robot. The intelligent terminal inputs or selects the target position through the user interface, and calibrates the target position and the robot position at the same time.

3. A method for controlling a robot through an intelligent terminal according to claim 1, characterized in that: In step S02, the robot receives the control signal and the generated expected trajectory, and determines through the camera whether the generated expected trajectory contains any obstacles. If it is determined that there are obstacles, the determination result and obstacle information are sent to step S01 to regenerate the expected trajectory. If it is determined that there are no obstacles, a motion trajectory is generated.

4. The method for controlling a robot through an intelligent terminal according to claim 1, characterized in that: In step S03, the specific contents of performing trajectory compensation analysis on the robot according to the expected trajectory and the motion trajectory are as follows: Extract the coordinates of the feature points of the desired trajectory , i represents the feature point number of the expected trajectory, i=1, 2, 3, ..., n, n represents the total number of feature points of the expected trajectory, and the feature point represents the inflection point in the curve formed by the expected trajectory. If the expected trajectory is a straight line, the feature point is the midpoint of the straight line; Extract the coordinates of the feature points of the motion trajectory corresponding to the feature points of the desired trajectory , calculate the distance between the feature points of each expected trajectory and the feature points of the motion trajectory, and the calculation formula is: ,in Indicates the distance between the feature points of each expected trajectory and the feature points of the motion trajectory; Combined with the time data characteristics, the trajectory compensation analysis is performed on the characteristic points of the motion trajectory. The calculation formula is: ,in Represents the output value of trajectory compensation analysis for the feature points of the motion trajectory. It represents the time it takes for the robot to reach each feature point of the desired trajectory from the robot position. It represents the time it takes for the robot to reach each characteristic point of the motion trajectory from the robot position; The output value of the trajectory compensation analysis Compared with the preset compensation threshold, if the output value of the trajectory compensation analysis is greater than or equal to the preset compensation threshold, the intelligent terminal determines to send a trajectory compensation instruction; if the output value of the trajectory compensation analysis is less than the preset compensation threshold, the intelligent terminal determines not to send a trajectory compensation instruction.

5. The method for controlling a robot through an intelligent terminal according to claim 1, characterized in that: In step S04, the specific contents of establishing a dual-track coupling analysis model based on the expected track and the motion track are as follows: Receive the trajectory compensation command sent by the intelligent terminal, and establish a dual-trajectory coupling analysis model to calculate the trajectory coupling coefficient based on the desired trajectory and the direction deflection coefficient of each feature point of the motion trajectory. The calculation formula is: ; Said represents the trajectory coupling coefficient, It represents the active force coefficient of the robot from the i-th feature point to the i+1-th feature point in the motion trajectory. represents the active force coefficient of the robot from the i-th feature point to the i+1-th feature point in the expected trajectory, Indicates the direction deflection coefficient of the robot from the i-th feature point to the i+1-th feature point in the motion trajectory, Represents the directional deflection coefficient of the robot from the i-th feature point to the i+1-th feature point in the expected trajectory.

6. A method for controlling a robot through an intelligent terminal according to claim 5, characterized in that: The specific calculation contents of the direction deflection coefficients of the desired trajectory and each feature point of the motion trajectory are as follows: Calculate the length between the i-th feature point and the i+1-th feature point in the motion trajectory. The calculation formula is: ,in Indicates the length between the i-th feature point and the i+1-th feature point in the motion trajectory; The directional deflection coefficient of each feature point in the motion trajectory is calculated based on the length between the feature points. The calculation formula is: ,in Represents the direction deflection coefficient of each feature point in the motion trajectory, Indicates the deflection angle from the i-th feature point to the i+1-th feature point in the motion trajectory; The direction deflection coefficient of each feature point in the expected trajectory is calculated based on the length between the feature points. The calculation formula is: ,in Represents the direction deflection coefficient of each feature point in the expected trajectory, represents the deflection angle from the i-th feature point to the i+1-th feature point in the expected trajectory, It represents the length between the i-th feature point and the i+1-th feature point in the expected trajectory.

7. The method for controlling a robot through an intelligent terminal according to claim 1, characterized in that: In step S05, the specific content of calculating the trajectory deviation compensation index according to the trajectory coupling coefficient by the intelligent terminal is as follows: Indicates the deflection angle from the i-th feature point to the i+1-th feature point in the motion trajectory. represents the deflection angle from the i-th feature point to the i+1-th feature point in the expected trajectory, where i=1, 2, 3, ..., n-1; The angle deviation compensation index between the motion trajectory and the expected trajectory is calculated based on the trajectory coupling coefficient. The calculation formula is: ,in It represents the angle deviation compensation index between the motion trajectory and the expected trajectory, and e represents a constant; Substitute the angle deviation compensation index into the trajectory deviation compensation model to calculate the trajectory deviation compensation index. The calculation formula is: ,in Indicates the trajectory deviation compensation index; The intelligent terminal controls the motion trajectory of the robot through the trajectory deviation compensation index. If the trajectory deviation compensation index of the robot's motion trajectory exceeds the preset threshold range, the feature point coordinates of the robot are adjusted until the trajectory deviation compensation index of the robot's motion trajectory is within the preset threshold range.

8. The method for controlling a robot through an intelligent terminal according to claim 1, characterized in that: In step S06, the intelligent terminal monitors the robot's motion state in real time while the robot is executing motion instructions. The control center compares and analyzes the received real-time data with the preset motion trajectory and adjusts the control instructions in real time. Once an abnormality in the robot's motion state is detected, an alarm will be immediately issued and measures will be taken to complete the intelligent control of the robot.

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