Motion planning of reaching point movements for 7R robotic manipulators in obstacle environment based on rapidly-exploring random tree algorithm

Based on single directional rapidly-exploring random tree (single-RRT) and bi-directional rapidly-exploring random tree (bi-RRT), the motion planning of reaching point movements for 7R robotic manipulators in obstacle environment is systematically studied. Numerical simulations and physical experiments are conducted by using the single-RRT algorithm. A new version of bi-RRT algorithm is proposed by incorporating the pose adjustments and the self-motion in joint space into the expansion of target trees. A general analytical inverse kinematic algorithm for 7R robotic manipulators is used to get desired target configurations. In this way, the given target configuration in the standard bi-RRT is replaced by a group of configurations in the new algorithm. In a given obstacle environment, the robot can automatically choose one of the appropriate configurations as the target node to direct the expansion of searching tree in the most efficient manner. Through numerical simulations, the superiority of this algorithm is further verified. By using Matlab, VC++ and OpenGL, a simulation software is developed to further conduct experimental researches on the motion planning of reaching point movements for 7R robotic manipulators.