Placing a robot manipulator amid obstacles for optimized execution

Abstract

This paper presents an efficient algorithm for optimizing the base location of a robot manipulator in an environment cluttered with obstacles, in order to execute specified tasks as fast as possible. The algorithm uses randomized motion planning techniques and exploits geometric "coherence" in configuration space to achieve fast computation. The performance of the algorithm is demonstrated on both synthetic examples and real-life CAD data from the automotive industry. The computation time ranges from under a minute for simple problems to a few minutes for more complex ones.