Improved RRT Path Planning Algorithm for Humanoid Robotic Arm

摘要

With the aging of the population and the increase in the employment cost of the elderly service industry, the elderly service robot has become an important development field. However, the working environment of the service robot is complex, and the robot arm may collide with the environmental obstacles, which will cause damage not only to the obstacles but also to the robot arm and even the served object. In this paper, an improved rapidly exploring random tree algorithm is proposed for path planning of humanoid robotic arm. First, the threshold of random probability sampling is set as the selection criterion of the extension mode. Then the random sampling value and the probability sampling threshold are compared, and the target point is determined as a random point if the random sampling value is within the set threshold value. Otherwise, the new node will be expanded under the joint action of the target gravity and the random point gravity. This is the extension of classification based on random probability. Finally, the breadth-first search is used to smooth the initial exploration path. The simulation results show that the proposed method can effectively reduce the path planning time and path length.