Abstract
This paper presents a variable step size trunk rapidly-exploring random trees (VT-RRT) algorithm for path planning of a dual-arm robot. First, we establish the DH parameter simulation model of the dual-arm robot which is composed of two UR5 single-arm robots. Then, in the working space of the dual-arm robot, several spheres are randomly added to constitute an obstacle environment. Finally, we propose a new improved algorithm by transforming the search space of random nodes in RRT algorithm and adaptively adjusting the step size according to the target position. The simulation results show that the VT-RRT algorithm effectively increases the search efficiency, decreases the iteration step size, and reduces the path planning time in comparison to the basic rapidly-exploring random trees (RRT) algorithm. At the same time, the robustness is also greatly increased.
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