Motion optimization using state-dispersion-based phase space partitions

This paper addresses a phase space partitioning problem in motion planning systems. A class of kinematic and dynamic motion planning systems, including rapid semioptimal motion-planning (RASMO), uses partitions for phase spaces in cumulative optimization criteria. In these systems, a partition results in a uniquely planned motion with a quality that is determined by a selected optimization criterion. In this paper, state-dispersion-based phase space partitioning (SDPP) that generates adaptive partitions is proposed. These partitions allow the motion planning systems to plan better motions. Uniform partitions and adaptively fixed partitions of SDPP are compared under several conditions using RASMO and a double inverted pendulum model while setting the optimality criterion of RASMO to time. The results reveal that RASMO with SDPP plans smaller time motions than those obtained with RASMO using uniform partitions.