Locally Optimal Planning in High Dimensions
نویسنده
چکیده
Algorithms which guarantee to find globally optimal trajectories by covering a hypervolume of state space become infeasible in high dimensions. We have developed an algorithm which generates locally optimal trajectories without covering a hypervolume which only requires polynomial memory and time. Even though the algorithm does not guarantee a globally optimal trajectory in a deterministic manner, it is experimentally shown that resulting trajectories are reasonable for pendulum swing-up tasks. Results are shown for pendulum with 1and 2-links and compared to globally optimal trajectories obtained by dynamic programming. Furthermore, results for 3-link pendulum of which globally optimal trajectory is currently unknown are presented. Advisor: Christopher G. Atkeson CONTENTS
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