Performance Comparison of Classical and Neural Sampling Algorithms for Robotic Navigation 事件

Performance Comparison of Classical and Neural Sampling Algorithms for Robotic Navigation arXiv:2605.25010v1 Announce Type: cross Abstract: Integrating artificial intelligence (AI) into sampling-based motion planning provides new possibilities for improving autonomous navigation efficiency. In this paper, three algorithms, namely RRT*, Neural RRT*, and Neural Informed RRT*, are implemented and evaluated on environments containing convex and concave obstacles with different obstacle densities. T