Sample-Driven Connectivity Learning for Motion Planning in Narrow Passages
Sihui Li,Neil T. Dantam,Sihui Li,Neil T. Dantam
Sampling-based motion planning works well in many cases but is less effective if the configuration space has narrow passages. In this paper, we propose a learning-based strategy to sample in these narrow passages, which improves overall planning time. Our algorithm first learns from the configuration space planning graphs and then uses the learned information to effectively generate narrow passage...
