Robot teleoperation guiding method based on force feedback

Abstract

The invention discloses a robot teleoperation guiding method based on force feedback, which comprises two parts of force feedback obstacle avoidance position guiding based on a buffer area and force feedback auxiliary grabbing of a spherical guiding force field, and is characterized in that the force feedback obstacle avoidance position guiding based on the buffer area is that an obstacle avoidance buffer area is established based on an obstacle bounding box; then whether the mechanical arm collides with the obstacle buffer area or not is judged, and if yes, force feedback is calculated according to the position of the mechanical arm in the buffer area; and a better obstacle avoidance effect is achieved. According to spherical guide force field force feedback auxiliary grabbing, a spherical guide force field and a spring-mass model are constructed, then feedback force of the spherical guide force field is calculated on the basis of the spring-mass model, an operator is assisted to control the tail end position of the mechanical arm between the inner layer and the outer layer of the spherical guide force field, attention of the operator to the position of the mechanical arm is reduced, and the grabbing efficiency is improved. Therefore, the clamping operation can be efficiently completed by adjusting the posture of the mechanical arm, and the effects of reducing burden, reducing misoperation and improving the working efficiency of remote operation grabbing are achieved.

Description

Technical Field

[0001] The invention relates to a robot motion control method, and in particular to a robot teleoperation guidance method based on force feedback. Background Art

[0002] Grasping is one of the main tasks of a robot. Teleoperating a robot to grasp can give the robot artificial flexibility. However, in teleoperation, insufficient telepresence can lead to low grasping efficiency and even errors. Therefore, it is necessary to guide the teleoperation. The force-guided teleoperation system and control method based on a dual-arm collaborative potential field disclosed in CN117984322A uses two robotic arms and a force feedback hand controller to construct a reaction force and a target point attraction by means of a virtual potential field. However, after the teleoperation reaches the target point, it can only guide a single position and posture. The operator cannot adjust the position and posture of the robotic arm according to the actual situation of the working area, which affects the grasping efficiency and user experience. Summary of the invention

[0003] Purpose of the invention: The purpose of the present invention is to provide a robot teleoperation guidance method based on force feedback with high grasping efficiency and good user experience.

[0004] Technical solution: A robot teleoperation guidance method based on force feedback of the present invention comprises:

[0005] The teleoperated manipulator moves toward the grasping target point. When the distance between the end point of the manipulator and the grasping target point is less than or equal to the set value, a spherical guiding force field including an inner layer, a middle layer and an outer layer is established with the grasping target point as the center of the sphere, and the length s of the gripper installed at the end of the manipulator is determined as the radius of the outer layer.

[0006] A spring-mass model is established in a spherical guiding force field to separate the middle layer from the inner and outer layers;

[0007] Based on the spherical guiding force field and the spring-mass model, the teleoperated manipulator approaches the inner layer or the outer layer. When it contacts the spring-mass model, it deforms and generates force feedback, limiting the end point of the manipulator between the inner and outer layers.

[0008] After grasping the target object, the guidance can be turned off to leave the spherical guiding force field; if the target object is not grasped but one still wants to leave the spherical guiding force field, after the teleoperated robotic arm moves away from the target object, it gradually enters the spherical guiding force field, the deformation of the spring-mass model gradually increases, and the feedback force gradually increases. When the feedback force increases to the maximum value, if the teleoperated robotic arm continues to move outward, the spring-mass model breaks, the robotic arm leaves the spherical guiding force field, and the grasping guidance stops.

[0009] Furthermore, the spherical guiding force field adopts the spring-mass model for force feedback calculation, and the force feedback calculation formula is as follows:

[0010] By analyzing the dynamic equations of the spring-mass model, its moving mass satisfies:

[0011]

[0012] In this system equation, M is the mass of the particle, X is the spatial coordinate of the particle, t is the time constant, D is the damping coefficient, K is the elastic coefficient of the spring, and f is the feedback force;

[0013] Convert the solution of the system equation into a discrete particle differential equation and find the approximate solution; if the equation has a unique solution, set As unit time, in any time range By using the time difference method and the increment method, for each discrete particle, the equation can be transformed into:

[0014]

[0015] Among them, m i is the mass of the ith particle, X i is the coordinate position of the i-th particle;

[0016] Substituting into the differential equation we get:

[0017]

[0018] when As it approaches infinity, replace use replace have:

[0019]

[0020] Solving the equation can obtain the particle displacement and the magnitude of the particle feedback force.

[0021] Furthermore, the set value is 1.5s.

[0022] Furthermore, ss′=s / 10, where s′ is the inner radius.

[0023] Furthermore, in the existing robot arm remote operation guidance methods, such as CN114643576A, the guidance method does not take obstacle avoidance into consideration and cannot accurately guide the operator away from obstacles to avoid collisions. Another example is CN105150210B, although obstacle avoidance is taken into consideration, only the end point of the robot arm is taken into consideration, and obstacle avoidance is not performed on the robot arm joints. Therefore, the robot arm joints may collide with obstacles during the remote operation process.

[0024] To this end, the teleoperated mechanical arm moves toward the grasping target point, including:

[0025] Get the grab target point X target and obstacle position X obstacle , calculate the end point position X of the robot arm according to the robot arm positive solution expression and the robot arm joint angle EE ;

[0026] Calculate the bounding box for the obstacle, and establish an obstacle avoidance buffer by enlarging the bounding box proportionally. The range of the obstacle avoidance buffer is based on the geometric center C of the bounding box and the detection space range R B Sure;

[0027] During the movement of the robotic arm, the robotic arm joint sensors are used to collect the angles of each joint of the robotic arm, and the position of the robotic arm end point is obtained through positive solution. Real-time collision detection is performed based on the coordinates of the robotic arm end point and the buffer zone position to determine whether the robotic arm collides with the obstacle buffer zone; if a collision occurs, the force feedback is calculated based on the position of the robotic arm in the buffer zone:

[0028] L is the shortest distance between the end point of the robot arm and the obstacle after the collision is detected. r arm is the distance from the obstacle to the bounding box in the L direction, and r is the length of the buffer zone in the L direction;

[0029] When the robot is outside the buffer zone, L>r arm +r, the feedback force is zero; when the robot is in the buffer zone, that is, r arm <L<r arm +r, the feedback force f increases as the distance into the buffer zone increases; when the robot collides with the obstacle bounding box, that is, 0<L<r arm +r, the feedback force f is maximum and the robot arm stops moving;

[0030] Force feedback is performed according to the calculated force feedback value.

[0031] The present invention uses a buffer-based force feedback obstacle avoidance method to assist the operator in moving to the target location, which can greatly improve the safety of remote operation. Compared with other remote operation obstacle avoidance methods, it has better accuracy and better environmental adaptability, and can achieve smooth obstacle avoidance during remote operation without any jumps that affect the safety of remote operation.

[0032] Furthermore, the detection space range R B The expression is as follows:

[0033]

[0034] Among them, C is the geometric center of the OBB bounding box; are mutually perpendicular space vectors, serving as the direction vectors of the local coordinate system of the enclosed geometric object; r1, r2, r3 are the side lengths of the bounding box.

[0035] Furthermore, the range of the obstacle avoidance buffer is 1.2R B ~1.5R B .

[0036] Furthermore, the calculation model of the feedback force f is as follows:

[0037]

[0038] Where K is the proportionality coefficient.

[0039] Furthermore, the calculation formula of the proportionality coefficient K is as follows:

[0040]

[0041] Among them, f max is the maximum feedback force.

[0042] Furthermore, if the robot collides with more than one obstacle during movement, the feedback force f is the sum of the feedback forces of each obstacle:

[0043]

[0044] Where n represents the number of obstacles, f i represents the feedback force of the ith obstacle;

[0045] The direction of the feedback force is defined as the shortest distance between the obstacle and the end of the robot arm. The shortest distance between the obstacle center O and the robot arm AB is L, that is, the point C from the center O of the obstacle bounding box to the center axis of the bounding box at the end of the robot arm is on the line segment AB. The direction of the feedback force f is

[0046] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: After the teleoperated robot arm moves to the target location, the present invention uses a spherical guide area combined with a spring-mass model to guide the grasping force, assisting the operator in position control, so that the robot arm is at a distance suitable for grasping, which can reduce the operator's attention to the position of the robot arm during grasping, so that the operator can focus more on controlling the posture, and adjust the posture of the robot arm to efficiently complete the grasping operation. The present invention can reduce the burden on the operator, reduce misoperation, and greatly improve the efficiency of teleoperated grasping work. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic diagram of the teleoperation control system;

[0048] Figure 2 This is a diagram of a robot arm teleoperation grasping model;

[0049] Figure 3 It is a force feedback obstacle avoidance position guidance flow chart;

[0050] Figure 4 It is a schematic diagram of bounding box and buffer construction;

[0051] Figure 5 is a schematic diagram of virtual obstacle avoidance feedback force;

[0052] Figure 6 It is a schematic diagram of the construction of a spherical guiding force field;

[0053] Figure 7 It is a schematic diagram of the spring-mass algorithm;

[0054] Figure 8 It is a schematic diagram of the force feedback of the spherical guiding force field;

[0055] Fig. 9 is a graph showing the relationship between the feedback force of the spherical guidance force field and the position of the robotic arm;

[0056] Fig.10 It is a flow chart of force-guided crawling. DETAILED DESCRIPTION

[0057] The present invention will be further described below in conjunction with the accompanying drawings.

[0058] The embodiment of the present invention provides a robot teleoperation guidance method based on force feedback. The robot teleoperation guidance method is based on Figure 1 The teleoperation control system shown is implemented, and the teleoperation control system mainly includes a host computer 2 (control computer), a force feedback master hand 3 (six-dimensional tactile input and output device) and a robot 5 (six-joint collaborative robotic arm), and a gripper 4 is installed at the end of the robotic arm. Figure 1 In the figure, 1 represents the operator, and 6 represents the object to be clamped and the obstacle.

[0059] The force feedback master hand is used to control the movement of the robot arm. It communicates with the robot arm through the host computer and controls its movement and grasping. At the same time, it uses the force feedback master hand to provide force feedback to the operator and guide the operation. The host computer is used to receive the force feedback master hand signal, solve and control the movement of the robot arm, and is also used to run the virtual environment.

[0060] The operation process of force feedback master hand remote control is as follows:

[0061] According to the collected three-dimensional model information (which can be collected in real time by the visual sensor or predefined), a model of the surrounding environment is established in the host computer, and a virtual robotic arm model is added. The DH coordinate system is established according to the physical data of the robotic arm and the force feedback master hand, and the kinematic forward and inverse expressions of the force feedback master hand and the robotic arm are calculated according to the DH table. The joint angles of the robotic arm are collected, and the angles of the virtual robotic arm model are adjusted according to the joint angles of the robotic arm in the virtual space to synchronize the virtual robotic arm model with the real robotic arm. The joint angles of the force feedback master hand are collected, and the kinematic forward solution is used to obtain the end point posture of the force feedback master hand, and it is enlarged to the target posture of the end point of the robotic arm, and a command is sent to the robotic arm to control its movement.

[0062] Figure 2 The robot arm remote control grasping model diagram is used to obtain the position and posture of the object to be grasped, and convert it into coordinates in the virtual space, so that the remote control robot arm grasping target point X can be obtained. target , and obtain the obstacle position X at the same time obstacle Since the robot arm positive solution expression and the robot arm joint angle are known, the robot arm end point position X can be calculated EE .

[0063] The robot teleoperation guidance method comprises two parts: force feedback obstacle avoidance position guidance based on a buffer zone and force feedback assisted grasping of a spherical guidance force field.

[0064] (I) Force feedback obstacle avoidance position guidance based on buffer zone

[0065] Figure 3 This is the flow chart of force feedback obstacle avoidance position guidance. For the virtual robot model, a bounding box is constructed to simplify the model complexity and improve the efficiency of collision detection. During teleoperation, the robot cannot collide with obstacles. In order to generate obstacle avoidance force feedback for guidance, a buffer zone is set around the obstacle. The buffer zone is constructed by proportionally enlarging the bounding box of the obstacle.

[0066] During the movement of the robotic arm, the robotic arm joint sensors are used to collect the angles of each joint of the robotic arm, and the position of the robotic arm end point is obtained through positive solution. Real-time collision detection is performed based on the coordinates of the robotic arm end point and the buffer zone position to determine whether the robotic arm collides with the obstacle buffer zone.

[0067] When the end or joint of the robot arm collides with the obstacle buffer, virtual force feedback can be generated to assist the operator to stay away from the obstacle. When the robot arm joint collides with the buffer zone, the joint moves to avoid hitting the obstacle. If the end or joint of the robot arm collides with the obstacle bounding box, it means that the robot arm is about to collide with a real obstacle and needs to stop urgently to ensure safety. In the above process, since the collision detection target is always the obstacle bounding box, it does not contact the real obstacle, which can achieve a better obstacle avoidance effect. Specifically:

[0068] Figure 4 (a) is a schematic diagram of obstacle avoidance during the robot teleoperation process. Figure 4 (b) is a schematic diagram of the obstacle bounding box and buffer zone. The OBB bounding box is the smallest hexahedron that encloses the geometric model object and whose faces are parallel to the enclosed geometric model object. The geometric center C of the bounding box and the detection space range R are determined. B , detection space range R B The expression is as follows:

[0069]

[0070] Where C is the geometric center of the OBB bounding box; are mutually perpendicular space vectors, serving as the direction vectors of the local coordinate system of the enclosed geometric object; r1, r2, r3 are the side lengths of the bounding box.

[0071] The OBB bounding box is arbitrary in direction, close to the model, and has good collision detection accuracy. The buffer is a geometric enlargement of the bounding box. Its geometric center is the same as the space vector, and its side length is a multiple of the bounding box side length, generally set to 1.2 to 1.5 times, that is, the geometric center C is the same, and the detection range is 1.2R B ~1.5R B , taking 1.2 times as an example:

[0072]

[0073] Figure 5 This is a schematic diagram of the virtual obstacle avoidance feedback force. When the obstacle buffer detects a collision, the virtual collision force calculation model is used to calculate the magnitude and direction of the feedback force based on the distance of the collision overlap.

[0074] Since there is an upper limit to the feedback force of the force feedback device, assume that the upper limit force is f max ; When the robot is outside the buffer zone, L>r arm +r, the feedback force is zero; when the robot is in the buffer zone, that is, r arm <L<r arm +r, the feedback force f increases as the distance into the buffer zone increases; when the robot collides with the obstacle bounding box, that is, 0<L<r arm +r, it means that the current position of the robot arm is very dangerous, the feedback force f is the maximum, and the robot arm stops moving. The calculation model of the feedback force f is as follows:

[0075]

[0076] The calculation formula of the proportionality coefficient K is as follows:

[0077]

[0078] Among them, L is the shortest distance between the end point of the robot arm and the obstacle after the collision is detected, and the calculation formula is: r arm is the distance from the obstacle to the bounding box in the L direction, and r is the length of the buffer zone in the L direction.

[0079] When the end of the robot arm does not touch the obstacle buffer, no feedback force is generated; when the robot arm touches the buffer but does not touch the bounding box, the feedback force is between 0-f max When the robot arm touches the bounding box, the feedback force is maximum and the system stops suddenly to ensure safety.

[0080] The force feedback value obtained by calculation is fed back through the force feedback master hand. During the movement, if the robot arm collides with more than one obstacle, the feedback force f is the sum of the feedback forces of each obstacle:

[0081]

[0082] Where n represents the number of obstacles, f i represents the feedback force of the ith obstacle.

[0083] The direction of the feedback force is defined as the shortest distance between the obstacle and the end of the robot arm. The shortest distance between the obstacle center O and the robot arm AB is L, that is, the point C from the center of the obstacle bounding box O to the center axis of the bounding box at the end of the robot arm is on the line segment AB. The direction of the feedback force f is

[0084] (II) Spherical guided force field force feedback assisted grasping

[0085] Figure 6 Schematic diagram of the construction of a spherical guiding force field. The target point is known to be X. targe , a spherical guiding force field is established in the virtual space to assist the operator in grasping. The operator guides the teleoperated robot arm to the vicinity of the grasping target point through the path. When the distance between the end point of the robot arm and the grasping target point is less than or equal to 1.5s, the grasping target point X is reached. target A spherical guiding force field is established with the sphere as the center to guide the operator to perform the grasping operation.

[0086] The spherical guiding force field is divided into three layers, including the inner layer, the middle layer and the outer layer. The inner layer and the outer layer are the repulsive layer, which is used to guide the operator to reach the middle layer by generating repulsive force. EE , the gripper is installed after the end point, and the distance from the end point of the robot arm to the gripping point of the gripper is s (that is, the gripper length is s). In order to facilitate grasping, the outer radius of the spherical guiding force field is set to s, and the center of the sphere is the grasping target point X targetThe inner radius is s′, s′<s. The difference between the inner and outer radii is determined by s, which is generally set to ss′=s / 10. During teleoperation, the end point of the robot arm is restricted to the middle layer, and the gripper installed at the end of the robot arm can extend into the force field to grab the object. Therefore, when performing the grabbing operation, the operator only needs to adjust the posture of the robot arm, and does not need to pay attention to the adjustment of the position of the robot arm.

[0087] Figure 7 This is a schematic diagram of the spring-mass algorithm. In order to enable the operator to enter and exit the guidance area while receiving force feedback, a spring-mass model is established in the spherical guidance force field to separate the middle layer from the inner and outer layers (that is, the spring-mass model is the isolation layer of the guidance force field). The guidance force field uses the spring-mass model to perform force feedback calculations.

[0088] In the spring-mass model, the nodes in the grid represent the mass points in the model. When force feedback is generated, the grid points will deform to generate feedback. The spring connecting the two nodes represents the interaction force generated between the nodes. In order to better generate the hindering effect of force feedback, damping is added to the model to ensure stability.

[0089] For example, during teleoperation, the force feedback master hand contacts the outer surface, and the operator moves the force feedback master hand away from the object to be clamped. The outer spherical particles are deformed by the force, and feedback force is generated to the operator. The force feedback calculation formula is as follows:

[0090] By analyzing the dynamic equation of the mass-spring model, its moving mass satisfies:

[0091]

[0092] In this system equation, M is the mass of the particle, X is the spatial coordinate of the particle, t is the time constant, D is the damping coefficient, K is the elastic coefficient of the spring, and f is the feedback force; the solution of the system equation is converted into a discrete particle differential equation to obtain an approximate solution; if the equation has a unique solution, set As unit time, in any time range By using the time difference method and the increment method, for each discrete particle, the equation can be transformed into:

[0093]

[0094] Among them, m i is the mass of the ith particle, X i is the coordinate position of the i-th particle;

[0095] Substituting into the differential equation we get:

[0096]

[0097] when As it approaches infinity, replace use replace have:

[0098]

[0099] Solving the equation can obtain the particle displacement and the magnitude of the particle feedback force.

[0100] Figure 8 It is a schematic diagram of the force feedback of the spherical guiding force field, as shown in Figure 8 As shown in (a), the end point of the robot arm is abstracted as a proxy point for calculating the feedback force. After the end point of the robot arm is within the spherical guiding force field, the operator can adjust the posture of the robot arm gripper at any time to grasp and ensure that the gripper is within a distance suitable for grasping. Figure 8 As shown in (b), when the end point of the robot arm approaches the inner and outer guiding force fields, the spring-mass model contacts the robot arm proxy point, calculates the displacement deformation of the mass point through the force feedback algorithm, and gives the operator real-time feedback force. When the proxy point gradually enters the inner and outer guiding force fields, the model deformation gradually increases, and the feedback force gradually increases. Figure 8 As shown in (c), when the proxy point enters the outer layer, the feedback force increases to the maximum value f max At this time, the spring-mass model reaches the maximum limit. If the operator continues to control the robot arm to move outward, the spring-mass model breaks, and the virtual force will be reduced from the maximum force f max The relationship between the feedback force of the spherical guiding force field and the position of the robot arm is shown in the figure below: Fig. 9 shown.

[0101] Based on the spherical guiding force field and the spring-mass model for the operator's force feedback, the end point of the teleoperated manipulator is limited between s and s' (i.e., between the inner and outer layers), so that the manipulator is in the most suitable range for grasping. When the operator operates the manipulator close to the inner or outer layer, it contacts the spring-mass model to deform it and generate force feedback, limiting the position of the manipulator. When the end of the manipulator is in the guiding force field, the end gripper will be at a better gripping distance. At this time, the operator can reduce the attention to the position of the manipulator during grasping, so that he can focus on controlling the posture and reduce the burden.

[0102] Fig.10The figure shows the overall flow chart of the grasping process. When using the force feedback master hand to remotely operate the robot for grasping, the sensor is first used to detect the entire grasping scene and identify the workspace, the robotic arm, the object to be grasped, etc. The operator is guided according to the results to help the operator avoid obstacles and reach the grasping target point. Then a spherical guiding force field is generated to keep the end point of the robotic arm at a suitable distance from the object to be grasped to assist the operator in grasping. During grasping, the guiding force field will assist the operator to stay in the spherical force field. When the end point of the robotic arm is too far away from the object to be grasped, the spring-mass model will break and the spherical guiding force field will no longer work. At this point, if the grasping work has been successful, the remote operation will no longer be guided. If the grasping is not successful, the operator needs to be guided again until the grasping is successful.

Claims

1. A robot teleoperation guidance method based on force feedback, characterized in that: include: The teleoperated manipulator moves toward the grasping target point. When the distance between the end point of the manipulator and the grasping target point is less than or equal to the set value, a spherical guiding force field including an inner layer, a middle layer and an outer layer is established with the grasping target point as the center of the sphere, and the length s of the gripper installed at the end of the manipulator is determined as the radius of the outer layer. A spring-mass model is established in a spherical guiding force field to separate the middle layer from the inner and outer layers; Based on the spherical guiding force field and the spring-mass model, the teleoperated manipulator approaches the inner layer or the outer layer. When it contacts the spring-mass model, it deforms and generates force feedback, limiting the end point of the manipulator between the inner and outer layers. After grasping the target object, the guidance can be turned off to leave the spherical guiding force field; if the target object is not grasped but one still wants to leave the spherical guiding force field, after the teleoperated robotic arm moves away from the target object, it gradually enters the spherical guiding force field, the deformation of the spring-mass model gradually increases, and the feedback force gradually increases. When the feedback force increases to the maximum value, if the teleoperated robotic arm continues to move outward, the spring-mass model breaks, the robotic arm leaves the spherical guiding force field, and the grasping guidance stops.

2. The robot teleoperation guidance method based on force feedback according to claim 1, characterized in that: The spherical guiding force field uses the spring-mass model for force feedback calculation. The force feedback calculation formula is as follows: By analyzing the dynamic equations of the spring-mass model, its moving mass satisfies: In this system equation, M is the mass of the particle, X is the spatial coordinate of the particle, t is the time constant, D is the damping coefficient, K is the elastic coefficient of the spring, and f is the feedback force; Convert the solution of the system equation into a discrete particle differential equation and find the approximate solution; if the equation has a unique solution, set As unit time, in any time range By using the time difference method and the increment method, for each discrete particle, the equation can be transformed into: Among them, m i is the mass of the ith particle, X i is the coordinate position of the i-th particle; Substituting into the differential equation we get: when As it approaches infinity, replace use replace have: Solving the equation can obtain the particle displacement and the magnitude of the particle feedback force.

3. The robot teleoperation guidance method based on force feedback according to claim 1, characterized in that: The set value is 1.5s.

4. The robot teleoperation guidance method based on force feedback according to claim 1, characterized in that: ss′=s / 10, s′ is the inner radius.

5. The robot teleoperation guidance method based on force feedback according to any one of claims 1 to 4, characterized in that: The teleoperated mechanical arm moves toward the grasping target point, including: Get the grab target point X tartget and obstacle position X abstacle , calculate the end point position X of the robot arm according to the robot arm positive solution expression and the robot arm joint angle EE ; Calculate the bounding box for the obstacle, and establish an obstacle avoidance buffer by enlarging the bounding box proportionally. The range of the obstacle avoidance buffer is based on the geometric center C of the bounding box and the detection space range R B Sure; During the movement of the robot arm, the robot arm joint sensors are used to collect the angles of each joint of the robot arm, and the position of the end point of the robot arm is obtained through positive solution. Real-time collision detection is performed based on the coordinates of the end point of the robot arm and the position of the buffer zone to determine whether the robot arm collides with the obstacle buffer zone; If a collision occurs, the force feedback is calculated based on the position of the robot in the buffer zone: L is the shortest distance between the end point of the robot arm and the obstacle after the collision is detected. r arm is the distance from the obstacle to the bounding box in the L direction, and r is the length of the buffer zone in the L direction; When the robot is outside the buffer zone, L>r arm +r, the feedback force is zero; when the robot is in the buffer zone, that is, r arm <L<r arm +r, the feedback force f increases as the distance into the buffer zone increases; when the robot collides with the obstacle bounding box, that is, 0vL<r arm +r, the feedback force f is maximum and the robot arm stops moving; Force feedback is performed according to the calculated force feedback value.

6. The robot teleoperation guidance method based on force feedback according to claim 5, characterized in that: Detection space range R B The expression is as follows: Among them, C is the geometric center of the OBB bounding box; are mutually perpendicular space vectors, serving as the direction vectors of the local coordinate system of the enclosed geometric object; r1, r2, r3 are the side lengths of the bounding box.

7. The robot teleoperation guidance method based on force feedback according to claim 5, characterized in that: The range of the obstacle avoidance buffer is 1.2R B ~1.5R B .

8. The robot teleoperation guidance method based on force feedback according to claim 5, characterized in that: The calculation model of the feedback force f is as follows: Where K is the proportionality coefficient.

9. The robot teleoperation guidance method based on force feedback according to claim 8, characterized in that: The calculation formula of the proportionality coefficient K is as follows: Among them, f max is the maximum feedback force.

10. The robot teleoperation guidance method based on force feedback according to claim 5, characterized in that: If the robot collides with more than one obstacle during movement, the feedback force f is the sum of the feedback forces of each obstacle: Where n represents the number of obstacles, f i represents the feedback force of the ith obstacle; The direction of the feedback force is defined as the shortest distance between the obstacle and the end of the robot arm. The shortest distance between the obstacle center O and the robot arm AB is L, that is, the point C from the center O of the obstacle bounding box to the center axis of the bounding box at the end of the robot arm is on the line segment AB. The direction of the feedback force f is

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