On the use of randomized low-discrepancy sequences in sampling-based motion planning

This paper shows the performance of randomized low-discre-pancy sequences compared with others low-discrepancy sequences. We used two motion planning algorithms to test this performance: the expansive planner proposed in [1], [2] and SBL [3] . Previous research already showed that the use of deterministic sampling outperformed PRM approaches [4], [5], [6]. Experimental results show performance advantages when we use randomized Halton and Sobol sequences over Mersenne-Twister and the linear congruential generators used in random sampling.

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