Map pixelation method based improved RRT algorithm for manipulator motion planning
Aiming at the problems of weak exploration ability,slow convergence speed and poor path quality in the manipulator motion planning of rapidly-exploring random tree algorithm,an improved Rapidly-exploring Random Tree(RRT)algorithm based on map pixelation was proposed.A uniform node sampling strategy was adopted,which significantly enhanced the exploration ability of RRT through central sampling and avoiding repeated sampling.Besides,a node rejection strategy was proposed to effectively reduce the number of collision detections and improve the algorithm efficiency utilizing pixel map to record obstacle information.At the same time,a dynamic path strategy was proposed to form several paths based on whether the nodes could connect to the target point with-out collision or not,and set the optimal path was set as the final path to accelerate the convergence speed of the al-gorithm.After searching,redundant nodes in the path were eliminated,and the triangle inequality was used to opti-mize the path.Finally,the simulation results of various two-dimensional map showed that the improved RRT algo-rithm could generate a more optimal path in less time.Furthermore,the superiority and practicability of the algo-rithm were verified by the Robotics Toolbox simulation experiment and obstacle avoidance experiment of the real manipulator.
manipulatormotion planningrapidly-exploring random treeuniform node sampling
万方数据
维普
