Abstract
Aiming at the existing artificial potential field method, it still has the defects of easy to fall into local extremum, low success rate and unsatisfactory path when solving the problem of obstacle avoidance path planning of manipulator. An improved method for avoiding obstacle path of manipulator is proposed. First, the manipulator is subjected to invisible obstacle processing to reduce the possibility of its own collision. Second, establish dynamic virtual target points to enhance the predictive ability of the manipulator to the road ahead. Then, the artificial potential field method is used to guide the manipulator movement. When the manipulator is in a local extreme or oscillating, the extreme point jump-out function is used in real time to make the end point of the manipulator produce small displacements and change the action direction to effectively jump out of the dilemma. Finally, the manipulator is controlled to avoid all obstacles and move smoothly to form a spatial optimization path from the start point to the end point. The simulation experiment shows that the proposed method is more suitable for complex working environment and effectively improves the success rate of manipulator path planning, which provides a reference for further developing the application of manipulator in complex environment.
Highlights
A4m=on4g33.t0h7emmm.2 = 431.8 mm, 3 = 20.32 mm, 2 = 149.09 mm [15, 16] combined with the random advantage of RRT algorithm to generate virtual target points to escape local extremum, but there are too many uncertain factors in the process, and the path is not guaranteed to be optimal
Based on the above analysis, it can be seen that the defects of the arti cial potential eld method restrict the completion quality of the manipulator obstacle avoidance path planning task. is paper starts from reducing the possibility of falling into local extremum and path optimization, by establishing the dynamic virtual target points to improve the ability of the manipulator to predict obstacles in front; by setting the extreme point jump function to help the manipulator to jump out of local extremum or oscillation
The random principle of the dynamic virtual target point reduces the possibility that the manipulator is trapped in the local extremum, and the extreme point jump-out function e ectively solves the problem of extreme point, and oscillation and reduces the unnecessary moving distance as much as possible, which is bene cial to improve the overall path quality
Summary
A er the parameters are determined, the manipulator can be analyzed for positive kinematics. In the case of a given base coordinate, the end position, and attitude can be obtained by the transformation formula. Substituting the link parameters information of PUMA560 into Equation (1), the homogeneous transformation matrix between the links can be calculated. By multiplying the link transformation matrices, a matrix of end positions and poses can be obtained. By multiplying the link transformation matrices, a matrix of end positions and poses can be obtained. at is, its positive kinematics equation, as shown in Equation (2)
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