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This paper presents a novel motion planning algorithm for industrial robots based on the PRM (Probabilistic Roadmaps) algorithm. Unlike the traditional PRM algorithm this algorithm significantly reduces computational efforts by carrying out robot path calculations in both robot workspace and configuration space. This algorithm also includes a fast space division method for improving the sampling efficiency. Since both the robot and obstacles are modeled as cuboids, the static collision checking is formulated as a convex optimization problem. By applying adaptive dynamic collision checking method, the motion planning problem is solved efficiently and completely without loss of computation precision.