Non-Parametric Learning for Natural Plan Generation
We present a novel way to learn sampling distributions for sampling-based motion planners by making use of expert data. We learn an estimate (in a non-parametric setting) of sample densities around semantic regions of interest, and incorporate these learned distributions into a sampling-based planne...
| Main Authors: | , , |
|---|---|
| Format: | Conference item |
| Published: |
2010
|