Improving Efficiency of Sampling-based Motion Planning via Message-Passing Monte Carlo

Makram Chahine; T. Konstantin Rusch; Zach J Patterson; Daniela Rus

2025 CoRL CoRL 2025

Improving Efficiency of Sampling-based Motion Planning via Message-Passing Monte Carlo

Abstract

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Authors

Makram Chahine, T. Konstantin Rusch, Zach J Patterson, Daniela Rus

Topics

Machine Learning > Optimization & Theory > Optimization Deep Learning > Architectures > Graph Neural Networks Robotics > Capabilities > Motion Planning

Keywords

motion planning graph neural network uniformity low-discrepancy distributions message-passing monte carlo ‑lp discrepancy measure

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