Obstacle crossing control method and system of robot

Abstract

The invention relates to the technical field of robot obstacle crossing, and discloses a method and system for achieving industrial data distributed multi-level cache consistency, and the method comprises the steps: obtaining obstacle data, and controlling a robot to decelerate and stop in advance when approaching an obstacle; walking arm obstacle crossing is conducted according to the sequence of the front-end walking arm and the rear-end walking arm; and obstacle crossing of the auxiliary arm is carried out, and after the auxiliary arm crosses obstacles and rewiring is carried out, obstacle crossing control of the robot is completed. According to the invention, through the multi-sensor fusion technology combining the camera and the laser radar, the recognition precision and the positioning accuracy of the complex obstacle on the power transmission line are improved. Besides, D-H connecting rod modeling and a robust PD control method are adopted, coordinated movement of the walking arm and the auxiliary arm is achieved, the robot is kept balanced in the obstacle crossing process, the stability is improved, the risk of attitude instability or structure looseness in the obstacle crossing process is reduced, and the safety and the working efficiency of the hot-line work robot are improved.

Description

Technical Field

[0001] The present invention relates to the field of robot obstacle crossing technology, and in particular to a robot obstacle crossing control method and system. Background Art

[0002] With the continuous development of robot technology, especially its application in the power industry, live working robots have become an important tool for the maintenance and inspection of transmission lines. Traditional live working relies on manual operation, which is extremely dangerous and labor-intensive. The emergence of live working robots has greatly improved the safety and efficiency of transmission line operation and maintenance. Current robot technology often encounters various obstacles in the process of traveling on the transmission line, such as spacers, suspension wire clamps, shock-absorbing hammers, etc., which will hinder the normal movement of the robot. In order to effectively avoid these obstacles, existing live working robots usually use mechanical arms to help overcome obstacles. However, the existing obstacle control methods often show the problem of insufficient flexibility when facing complex obstacle shapes and positions. It is difficult for the robot to accurately identify the type and position of the obstacle, which easily leads to obstacle failure or damage to the mechanical structure. In addition, the existing robot obstacle crossing system has high requirements for stability and reliability, especially in the process of obstacle crossing, the robot needs to be kept balanced to avoid safety hazards caused by the center of gravity shift.

[0003] In the prior art, some robots for live working use a single sensor, such as a camera or a lidar, to identify and locate obstacles. However, the accuracy and adaptability of a single sensor are limited, and it is unable to provide sufficient information support in a complex power line environment. Especially when dealing with obstacles of complex shapes such as spacers, existing robots often have inaccurate positioning and recognition errors, resulting in obstacle crossing failure or discontinuous movements, affecting work efficiency. In addition, the current robot arm obstacle crossing control methods are mostly based on the coordination of a simple walking arm and an auxiliary arm, lacking precise control of dynamic balance and multi-point force, and the robot is prone to problems such as unstable posture and loose structure during obstacle crossing. More importantly, the obstacle crossing process in the prior art mostly relies on a fixed preset motion trajectory, and cannot be flexibly adjusted according to the obstacle data obtained in real time, resulting in the robot showing a low level of adaptability and intelligence in actual operation. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem to be solved by the present invention is that the existing obstacle crossing technology of live working robots has problems such as low obstacle recognition accuracy and poor stability of the obstacle crossing process.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a robot obstacle crossing control method, comprising: obtaining obstacle data, controlling the robot to slow down and stop in advance when approaching an obstacle; performing obstacle crossing with the walking arm in the order of the front walking arm and the rear walking arm; performing obstacle crossing with the auxiliary arm, and completing the robot's obstacle crossing control after the auxiliary arm has crossed the obstacle and reconnected.

[0007] As a preferred solution of the robot obstacle crossing control method described in the present invention, after obtaining the obstacle data, the live working robot also includes identifying, classifying and locating the obstacle, determining the relative position between the obstacle and the robot, and slowing down and stopping in advance when approaching the obstacle.

[0008] As a preferred solution of the robot obstacle crossing control method described in the present invention, wherein: the walking arm obstacle crossing includes front walking arm obstacle crossing and rear walking arm obstacle crossing.

[0009] As a preferred solution of the robot obstacle crossing control method described in the present invention, the front walking arm obstacle crossing includes: the tensioning wheels on the two walking arms at the front end of the robot are lowered, the walking wheels are raised until the walking wheels are no longer in contact with the transmission line and maintain an appropriate distance, and the front walking arm swings outward until the walking wheels are off the line and can avoid obstacles.

[0010] As a preferred solution of the robot obstacle crossing control method of the present invention, wherein: the front walking arm obstacle crossing also includes, when the walking wheel of the front walking arm is off-line, the robot uses the three non-collinear fulcrums formed by the two rear walking arms and the auxiliary arm on the transmission line to maintain stability, and moves forward until the front walking arm crosses the obstacle;

[0011] As a preferred scheme of the robot obstacle crossing control method described in the present invention, wherein: the rear end walking arm obstacle crossing includes, after the front end walking arm completes the obstacle crossing, the tensioning wheel on the rear end walking arm descends, and the walking wheel rises and swings outward until it is off the line; the robot moves forward until the rear end walking arm crosses the obstacle, the robot stops moving, the rear end walking wheel retracts and completes the line falling, and the rear end walking arm completes the obstacle crossing.

[0012] As a preferred scheme of the robot obstacle crossing control method described in the present invention, the auxiliary arm obstacle crossing includes: the clamping wheel on the auxiliary arm is loosened until the end of the auxiliary arm is off the line, the auxiliary arm is swung downward so that the end reaches a position where it can cross the obstacle, the robot moves forward until the auxiliary arm crosses the obstacle, and the end of the auxiliary arm falls off the line again, completing the auxiliary arm obstacle crossing.

[0013] A robot obstacle crossing control system using any of the methods described in the present invention, wherein: a positioning module obtains obstacle data through a camera and a laser radar installed in the middle of the robot, classifies and locates the obstacles, and determines the relative position between the obstacles and the robot; an analysis module establishes a DH connecting rod coordinate system in advance according to the robot structure, and performs kinematic and dynamic analysis to establish a dynamic model, and analyzes the movement of the robot arm according to the dynamic model each time the robot crosses an obstacle; a main control module adjusts the movement of the robot arm in real time according to the kinematic and dynamic analysis results provided by the analysis module to enable the robot to cross obstacles.

[0014] A computer device comprises: a memory and a processor; the memory stores a computer program, comprising: the steps of implementing any one of the methods of the present invention when the processor executes the computer program.

[0015] A computer-readable storage medium stores a computer program, comprising: when the computer program is executed by a processor, the steps of implementing any one of the methods of the present invention are implemented.

[0016] Beneficial effects of the present invention: The present invention improves the recognition accuracy and positioning accuracy of complex obstacles on the transmission line by combining the multi-sensor fusion technology of the camera and the lidar. Compared with the prior art, the obstacle control method of the present invention can effectively avoid the problem of inaccurate obstacle recognition and ensure that the robot's movements in the obstacle crossing process are more accurate. In addition, the present invention adopts DH connecting rod modeling and robust PD control method to achieve coordinated movement of the walking arm and the auxiliary arm, maintain the balance of the robot and improve stability during the obstacle crossing process, reduce the risk of posture instability or structural looseness during the obstacle crossing process, and improve the safety and working efficiency of the live working robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0018] Figure 1 An overall flow chart of a robot obstacle crossing control method provided by one embodiment of the present invention;

[0019] Figure 2 A schematic diagram of a live working robot crossing a spacer bar in a robot obstacle crossing control method provided by an embodiment of the present invention;

[0020] Figure 3A DH coordinate system relationship diagram of a robot obstacle crossing control method provided by one embodiment of the present invention;

[0021] Figure 4 A schematic diagram of a DH coordinate system of a live working robot walking arm of a robot obstacle crossing control method provided by an embodiment of the present invention;

[0022] Figure 5 A schematic diagram of a DH coordinate system of a live working robot auxiliary arm of a robot obstacle crossing control method provided by an embodiment of the present invention;

[0023] Figure 6 A walking arm model diagram of a robot obstacle crossing control method provided by one embodiment of the present invention;

[0024] Figure 7 A diagram of an auxiliary arm model of a robot obstacle crossing control method provided by one embodiment of the present invention;

[0025] Figure 8 A block diagram of a robust PD controller for a robot obstacle crossing control method provided by one embodiment of the present invention;

[0026] Fig. 9 A comparison diagram of the trajectory tracking of the rotating joints of the walking arm of a robot obstacle crossing control method provided in the third embodiment of the present invention.

[0027] Fig.10 A comparison diagram of the trajectory tracking of the telescopic joint of the walking arm of a robot obstacle crossing control method provided in the third embodiment of the present invention.

[0028] Fig.11 A comparison diagram of auxiliary arm rotation joint trajectory tracking of a robot obstacle crossing control method provided in the third embodiment of the present invention.

[0029] Fig.12 A comparison diagram of the trajectory tracking of the auxiliary arm telescopic joint of a robot obstacle crossing control method provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0031] Example 1, reference Figure 1-8 , as an embodiment of the present invention, provides a robot obstacle crossing control method, comprising:

[0032] S1: Obtain obstacle data and control the robot to slow down and stop in advance when approaching an obstacle.

[0033] S2: The walking arms overcome obstacles in the order of the front walking arm and the rear walking arm.

[0034] S3: The auxiliary arm overcomes the obstacle. After the auxiliary arm overcomes the obstacle and reconnects, the robot's obstacle-overcoming control is completed.

[0035] When the live working robot walks on the four-split conductors of the 220kV transmission line, it will encounter obstacles such as spacers, hanging wire clamps, and shock-absorbing hammers. The robot needs to use the structure designed above to complete the obstacle crossing. The most difficult obstacle to cross is the spacer. The following takes the representative obstacle of crossing the spacer as an example to formulate an obstacle crossing strategy, such as Figure 2 The specific steps for the live working robot to climb over the spacer obstacle are as follows:

[0036] (1) When the robot is on the line, it will lift the rope release mechanism through four push rods. The live working robot uses the camera and laser radar installed in the middle to identify and locate obstacles, determine the relative position between the obstacle and the robot, start to slow down at a distance of 500mm from the spacer, stop at a distance of 200mm from the obstacle, and start to autonomously cross the obstacle.

[0037] (2) The tension wheels on the two walking arms at the front of the live working robot are lowered, and the walking wheels are raised until the walking wheels are no longer in contact with the power transmission line and maintain an appropriate distance. The front walking arms are swung outward until the walking wheels are off the line and can avoid obstacles.

[0038] (3) The robot uses the three non-collinear pivots formed by the two rear walking arms and the auxiliary arm on the transmission line to maintain stability and move forward until the front walking arm passes the obstacle. The robot stops, the front walking arm retracts inward, the walking wheel moves downward until the walking wheel falls off the line, and the tension wheel rises.

[0039] (4) After the front walking wheel has completed the obstacle crossing, the tension wheel on the rear walking arm drops, and the walking wheel rises and swings outward until it is off the line. The robot moves forward until the rear walking arm has crossed the obstacle, then stops moving, the rear walking wheel retracts and completes the line falling, and the walking arm completes the obstacle crossing.

[0040] (5) The clamping wheel on the auxiliary arm is loosened until the end of the auxiliary arm is off the line. The auxiliary arm swings downward so that the end reaches a position where it can cross the obstacle. The robot moves forward until the auxiliary arm crosses the obstacle. The end of the auxiliary arm falls off the line again, and the obstacle crossing is completed.

[0041] To sum up the obstacle crossing process of the live working robot, during the obstacle crossing process, the robot always has at least three force fulcrums on the transmission line. The front walking arm, the rear walking arm and the auxiliary arm cross the obstacles in turn. When one group of mechanisms crosses the obstacle, the other two groups of mechanisms are responsible for maintaining the stability and normal movement of the robot.

[0042] Before the obstacle crossing process of the live working robot, it is necessary to carry out kinematic modeling of the walking arm of the live working robot. Through the DH model method, the structure of the robot arm is regarded as being in sequence, and the rotating joint and the telescopic joint are connected by connecting rods. There is a telescopic joint and a rotating joint on a walking arm.

[0043] The four walking arms of the robot are distributed symmetrically at the four corners of the robot body. The DH coordinate system is established by taking the right front walking arm as an example.

[0044] The present invention uses the middle of the robot box as the reference point and sets the polar coordinate origin as {x0, y0, z0}, which is also the base coordinate point for laser radar and visual fusion positioning. i ,y i ,z i}, the coordinate system is fixed on the rod i and moves with it. When the motor drives the walking arm joint to move, the rod i moves relative to the previous rod i-1.

[0045] First, we need to establish the robot's spatial coordinate system, where the z coordinate of each joint i is i The axis must be collinear with the motion axis of the next i+1 joint. i The z axis of the i-1 joint i-1 The extension line of z is perpendicular to i Axis and z i-1 The intersection of the two axes or the common perpendicular line of the two axes and z i The intersection of the axes is defined as x i The starting point of the axis. Finally, determine the y i axis, then determine x i Axis and z i The y axis can be established according to the right-hand rule. i Axis, such as Figure 3 shown.

[0046] After completing the establishment of the coordinate system of each joint, θ needs to be determined i ,d i , α i 、a i The values ​​of the geometric parameters mathematically describe the rotation and extension of the joint. The rules for determining the four parameters are as follows:

[0047] (1)θ i is the joint angle, that is, x i-1Axis around z i Axis rotation, turn to x i The required angle of the axis;

[0048] (2)d i is the connecting rod offset, that is, x i-1 Along z i Move in the axis direction, move to x i The required distance of the axis;

[0049] (3)α i is the connecting rod rotation angle, i.e. z i Axis around x i Axis rotation, turn to z i+1 The desired angle of the axis;

[0050] (4)a i is the connecting rod length, i.e. z i Axis along x i Move in the axis direction to z i The required distance between the axes.

[0051] After determining each parameter, the transformation matrix corresponding to each joint can be obtained:

[0052]

[0053] The coordinate transfer transformation relationship between joints is:

[0054]

[0055] Furthermore, the kinematic analysis of the live working robot is carried out:

[0056] (1) Kinematic analysis of walking arm

[0057] According to the above method, the DH link coordinate system of the walking arm of the live working robot is established, as follows: Figure 4 As shown. Based on the established coordinate system, list the parameters of each joint link of the live working robot.

[0058] Considering the center point of the base coordinate on the main body of the live working robot and the contact point between the walking wheel and the wire as the end, the transformation matrix of the robot is:

[0059]

[0060] By transforming the matrix 0 T2 can calculate the position of the end of the walking arm relative to the center base coordinates of the fuselage under the premise of knowing the joint variables θ1 and d2. The posture equation of the end of the walking arm is:

[0061]

[0062] Among them, p x 、p y 、p z Represents the three-dimensional position of the end of the walking arm in the Cartesian coordinate system.

[0063] (2) Kinematic analysis of auxiliary arm

[0064] Similarly, a DH link coordinate system is established for the auxiliary arm, such as Figure 5 shown.

[0065] The transformation matrix is:

[0066]

[0067] The posture equation of the auxiliary arm end is:

[0068]

[0069] Among them, p x 、p y 、p z Indicates the three-dimensional position of the end of the auxiliary arm in the Cartesian coordinate system.

[0070] Furthermore, the robot's kinematic analysis system studied the relationship between the end motion of the robot and each joint, but did not consider the impact of factors such as the force driving the joint motion and the mass of the connecting rod on the robot motion analysis. In order to control the robot more accurately, it is necessary to consider factors such as the mass, speed, acceleration, and torque of the robot during the motion process, and calculate the relationship between the driving force and structure of the moving joint during the motion process. The most widely used dynamic modeling methods are the Lagrange equation method and the Newton-Euler equation method. The Newton-Euler equation method uses the dynamic and static method to establish the dynamic equation, and its advantage is high calculation efficiency. In contrast, the Lagrange equation method does not need to consider the internal force of the robot during the motion process, and the calculation is relatively simple and convenient. Therefore, the paper uses the Lagrange equation method to perform a dynamic analysis of the walking arm of the live working robot during the obstacle crossing process, and establishes a corresponding mathematical model.

[0071] (1) Dynamic analysis of walking arm

[0072] When the live working robot crosses obstacles on the four-split conductor, the walking arm plays a vital role. The arm can avoid obstacles by extending and retracting and swinging outward. The control of the up and down extension and lateral swing of the walking arm is studied. Taking the right front walking arm as an example, a polar coordinate system is established with the center of the rotating joint as the origin. The model diagram is as follows Figure 6 As shown:

[0073] The joint variable vector is set to q = [θ1, r], where θ1 is the rotation joint variable angle, r is the total length from the rotation joint to the mass point M, where r1 = 400mm, r2 = 300mm. The mass of the robot arm is m = [m1, m2], where m1 = 2.5kg, m2 = 3kg. The system kinetic energy can be expressed as:

[0074] K=K1+K2

[0075] Where K1 is the kinetic energy of rod 1:

[0076]

[0077] I1 is the moment of inertia of rod 1:

[0078]

[0079] The combined results show that:

[0080]

[0081] Suppose the coordinates of the particle M in the polar coordinate system are M(x M ,y M ),in:

[0082]

[0083] The velocity of particle M is:

[0084]

[0085] The moment of inertia I2 of particle M is:

[0086]

[0087] The kinetic energy K2 of rod 2 can be calculated as:

[0088]

[0089] The total kinetic energy K of the walking arm is:

[0090]

[0091] Considering the origin O of the polar coordinate system as the zero energy point of the walking arm, the total potential energy can be obtained as:

[0092]

[0093] Substituting the total potential energy P and the total kinetic energy K into the Lagrangian mathematical model, we get the function:

[0094]

[0095] By taking the derivative of the Lagrangian function, we can obtain:

[0096]

[0097] Substituting the above formula into the dynamics equation, we can obtain the torque and external force of the revolute joint and telescopic joint:

[0098]

[0099] The inertia matrix H(q) is:

[0100]

[0101] is the Coriolis force, which can be expressed as:

[0102]

[0103] G(q) is the gravity matrix:

[0104]

[0105] (2) Dynamic analysis of auxiliary arm

[0106] The live working robot needs an auxiliary arm to form a fulcrum on the line to keep the robot balanced during the obstacle crossing process. After the walking arm passes the obstacle, the auxiliary arm passes the obstacle by telescoping and swinging up and down. The auxiliary arm is dynamically simulated to establish a coordinate system such as Figure 7 shown.

[0107] The auxiliary arm is modeled similarly to the walking arm, and is also composed of a rotation joint and a telescopic joint, so the dynamic modeling will not be further derived in detail.

[0108] Furthermore, based on the robot kinematics and dynamics analysis, the trajectory posture of the walking arm and the auxiliary arm during the obstacle crossing process can be controlled. The trajectory control of the walking arm and the auxiliary arm is actually the control of the joint motor on the robot arm. This chapter takes the trajectory of the end of the robot arm as the research target and studies the control method of the joint drive motor to improve the stability of the live working robot during the obstacle crossing process.

[0109] In the process of overcoming obstacles, the inertia of the walking arm and the auxiliary arm of the live working robot is small. In order to reduce the interference of the robot and external factors on the robot's obstacle control and improve the robustness of the control system, the paper adopts the robust PD control method to control the motion trajectory of the walking arm and the auxiliary arm during the obstacle crossing process. Add the interference term τ to the above dynamic model:

[0110]

[0111] Assume q d is the target value of the telescopic joint and the rotational joint, q is the actual value of the two joints, and the difference between the two is the joint error e:

[0112] e=q d -q

[0113]

[0114] Among them, a1, a2, and a3 are constants greater than zero, and the variables are introduced:

[0115]

[0116] Where γ>0, we can deduce:

[0117]

[0118] From the characteristics of the dynamic model, we know that there is a parameter vector that satisfies the model:

[0119]

[0120] The disturbance signals of the robot's walking arm and auxiliary arm are bounded, and assuming that the supremum is known, the controller and the adaptive rate are designed as follows:

[0121]

[0122] The parameter estimates are:

[0123]

[0124] Where:

[0125]

[0126] K p1 =diag(K p11 ,K p12 ),K p2 =diag(K p21 ,K p22 )

[0127] K v1 =diag(K v11 ,K v12 ),K v2 =diag(K v21 ,K v22 )

[0128]

[0129] Where K pij >0,Kvij >0,α i >0,β i >0(i=1,2)(j=1,2), Γ is a positive definite matrix.

[0130] The matrix can be derived by splitting

[0131]

[0132] (1) Under the walking arm dynamics model, the following formula can be derived:

[0133]

[0134] (2) Under the auxiliary arm dynamics model, the following formula can be derived:

[0135]

[0136] Φ 21 =Φ 22 =0

[0137]

[0138] Where g = 9.8 m / s 2 and It does not contain m1, m2, m3, and m4, so the controller can be used for variable load conditions. The control block diagram of the controller is as follows: Figure 8 shown.

[0139] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0140] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0141] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0142] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0143] Embodiment 2, in an exemplary embodiment, a robot obstacle control system is also provided, including:

[0144] The positioning module obtains obstacle data through the camera and laser radar installed in the middle of the robot. The module can identify, classify and locate obstacles, and obtain the shape, size and relative position data of obstacles. Through the visual information provided by the camera and the depth perception of the laser radar, the positioning module can accurately calculate the relative distance and azimuth between the obstacle and the robot, providing basic data support for obstacle crossing.

[0145] The analysis module establishes the DH link coordinate system in advance according to the robot structure to describe the spatial motion relationship between the joints and links of the robot manipulator. Based on this coordinate system, the analysis module conducts a comprehensive analysis of the kinematics and dynamics of the robot manipulator and establishes a dynamic model suitable for obstacle crossing operations. Each time an obstacle is crossed, the analysis module analyzes the action of the manipulator based on the obstacle data and dynamic model to determine how to complete the obstacle crossing operation by coordinating the walking arm and the auxiliary arm. This module ensures that the manipulator can make accurate motion decisions based on the shape and position of the obstacle when crossing an obstacle.

[0146] The main control module adjusts the action of the robot arm in real time according to the kinematic and dynamic analysis results provided by the analysis module. After receiving the analysis results from the analysis module, the module adjusts the posture, angle and strength of the robot arm in real time according to the calculated optimal motion path to ensure the smooth operation of the obstacle crossing. The main control module also combines the robust PD control method to adjust the force of each joint of the robot arm to ensure that the robot always maintains balance and stability during the obstacle crossing process, avoiding obstacle crossing failure or system instability caused by improper posture of the robot arm.

[0147] Example 3, reference Figure 9-12 , which is an embodiment of the present invention, provides a robot obstacle crossing control method. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0148] (1) Simulation and analysis of the motion trajectory of the walking arm overcoming obstacles According to the characteristics of the spacer bar, the live working robot stops moving and enters the autonomous obstacle overcoming program when it reaches 200 mm in front of the spacer bar. The vertical state of the walking arm and the fuselage is taken as the reference value, that is, the rotation joint takes θ1 = 0° as the reference value, and r = 520 mm as the reference value. The movement of the walking arm during the robot crossing the spacer bar is as follows:

[0149] 1) The telescopic arm extends upward, and the length r is extended from 520mm to 620mm;

[0150] 2) The walking arm swings outward, and the rotation joint angle θ1 rotates from 0° to 20°;

[0151] 3) The live working robot moves forward through the rear running wheels and the auxiliary arm until the front running wheels pass over the spacer bar;

[0152] 4) The walking arm is retracted inward, and the rotation joint angle θ1 is rotated from 20° to 0°;

[0153] 5) The telescopic arm shrinks downward, r shrinks from 620mm to 520mm, and the walking wheel falls back to the line. At this time, the front walking arm of the robot completes the obstacle crossing, and the rear walking arm crosses the spacer in the same way. Finally, the obstacle crossing process ends after the auxiliary arm crosses the obstacle. During the obstacle crossing process, the acceleration and deceleration process of the drive motor is completed in a very short time, so the speed change process is ignored. The expected trajectory input value of each joint of the walking arm is:

[0154]

[0155] Controller parameters are:

[0156] a1=2、a2=3、a3=6

[0157]

[0158] The simulation experiment was carried out using the Simulink platform tool, and the expected trajectory of the walking arm during the obstacle crossing process was compared with the actual trajectory, such as Fig. 9 and Fig.10 shown.

[0159] (2) Simulation and analysis of the auxiliary arm's obstacle-crossing motion trajectory

[0160] According to the characteristics of the obstacle, after the four walking arms have crossed the obstacle, the auxiliary arm begins to cross the obstacle. The hanging line at the end of the auxiliary arm is taken as the reference posture, that is, α1 = 30°, l = 800mm. The actions of the auxiliary arm during the robot crossing the spacer are as follows:

[0161] 1) The auxiliary arm swings down off-line to a joint angle of α1 = 20°;

[0162] 2) The telescopic joint of the auxiliary arm shrinks inward, from 800mm to 700mm;

[0163] 3) The robot moves forward until the auxiliary arm passes the obstacle;

[0164] 4) The telescopic joint of the auxiliary arm extends outward, and the length is extended from 700mm to 800mm;

[0165] 5) The auxiliary arm swings upward, rotates the joint angle α1 to 30°, and the end of the auxiliary arm re-hangs the line, and the obstacle crossing process of the auxiliary arm ends. Similarly, ignoring the acceleration and deceleration process of each joint drive motor, the expected trajectory of each joint of the auxiliary arm is:

[0166]

[0167] Controller parameters are:

[0168] a1=2、a2=3、a3=6

[0169]

[0170] The simulation trajectory results are as follows Fig.11 and Fig.12 shown.

[0171] It can be seen from the figure that the trajectory tracking effect of the robust PD algorithm is good. It can track the expected trajectory with an acceptable error. The convergence speed is fast. At the inflection point, the trajectory of the robust PD algorithm oscillates slightly but can quickly converge to the expected value, with good stability. Considering the interference of external factors on the robot's obstacle crossing process, the robust PD algorithm will produce some oscillations when approaching the target value, but the convergence and stability are less affected. From the simulation results, it can be seen that this method has a good effect on the control of the walking arm in the autonomous obstacle crossing process of the live working robot, and can effectively improve the obstacle crossing stability.

[0172] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A robot obstacle control method, characterized in that: include: Obtain obstacle data and control the robot to slow down and stop in advance when approaching an obstacle; The walking arms overcome obstacles in the order of the front walking arms and the rear walking arms; The auxiliary arm overcomes the obstacle. After the auxiliary arm overcomes the obstacle and reconnects the wires, the robot's obstacle-crossing control is completed.

2. The robot obstacle control method according to claim 1, characterized in that: After obtaining the obstacle data, the live working robot may also identify and classify the obstacle and locate it, determine the relative position between the obstacle and the robot, and decelerate and stop in advance when approaching the obstacle.

3. The robot obstacle control method according to claim 2, characterized in that: The walking arm obstacle crossing includes front walking arm obstacle crossing and rear walking arm obstacle crossing.

4. The robot obstacle control method according to claim 3, characterized in that: The front walking arm obstacle crossing includes: the tensioning wheels on the two walking arms at the front end of the robot are lowered, the walking wheels are raised until the walking wheels are no longer in contact with the transmission line and maintain an appropriate distance, and the front walking arm is swung outward until the walking wheels are off the line and can avoid obstacles.

5. The robot obstacle crossing control method according to claim 4, characterized in that: The front walking arm obstacle crossing also includes that when the walking wheel of the front walking arm is off-line, the robot uses the three non-collinear pivots formed by the two rear walking arms and the auxiliary arm on the transmission line to maintain stability and move forward until the front walking arm crosses the obstacle; The robot stops, the front walking arm retracts inward, the walking wheels move downward until they fall off the line, and the tensioning wheels rise, completing the obstacle crossing of the front walking arm.

6. The robot obstacle crossing control method according to claim 5, characterized in that: The rear walking arm overcoming obstacles includes: after the front walking arm has completed overcoming obstacles, the tensioning wheel on the rear walking arm is lowered, and the walking wheel is raised and swung outwards until it is off the line; The robot moves forward until the rear walking arm passes over the obstacle, then stops moving, the rear walking wheels retract and complete the drop line, and the rear walking arm completes the obstacle crossing.

7. The robot obstacle crossing control method according to claim 6, characterized in that: The auxiliary arm obstacle crossing includes: the clamping wheel on the auxiliary arm is loosened until the end of the auxiliary arm is off the line, the auxiliary arm is swung downward so that the end reaches a position where it can cross the obstacle, the robot moves forward until the auxiliary arm crosses the obstacle, and the end of the auxiliary arm falls off the line again, thereby completing the auxiliary arm obstacle crossing.

8. An obstacle-crossing control system for a robot using the method according to any one of claims 1 to 7, characterized in that: include, The positioning module obtains obstacle data through the camera and laser radar installed in the middle of the robot, classifies and locates the obstacles, and determines the relative position between the obstacles and the robot; The analysis module establishes the DH link coordinate system according to the robot structure in advance, performs kinematic and dynamic analysis, and establishes a dynamic model. Each time the robot crosses an obstacle, the movement of the robot arm is analyzed according to the dynamic model. The main control module adjusts the movement of the robotic arm in real time based on the kinematic and dynamic analysis results provided by the analysis module to enable the robot to overcome obstacles.

9. A computer device comprising: A memory and a processor; the memory stores a computer program, wherein the processor implements the steps of the robot obstacle control method as described in any one of claims 1-7 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the robot obstacle crossing control method as described in any one of claims 1 to 7 are implemented.

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