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A Survey on the Integration of Machine Learning with Sampling-based Motion Planning. (arXiv:2211.08368v1 [cs.RO])
cs.LG updates on arXiv.org arxiv.org
Sampling-based methods are widely adopted solutions for robot motion
planning. The methods are straightforward to implement, effective in practice
for many robotic systems. It is often possible to prove that they have
desirable properties, such as probabilistic completeness and asymptotic
optimality. Nevertheless, they still face challenges as the complexity of the
underlying planning problem increases, especially under tight computation time
constraints, which impact the quality of returned solutions or given inaccurate
models. This has motivated machine learning to improve the …
arxiv integration machine machine learning motion planning planning sampling survey