Oct 25, 2022 · The initial paths are often of poor quality. Therefore, we propose the NR-RRT algorithm to rapidly find near-optimal solutions with guaranteed ...

To fill this gap, we propose a neural risk-aware path planning method, neural risk-aware RRT (NR-RRT), to find risk bounded near-optimal solutions in uncertain ...

May 14, 2022 · Simulation experiments demonstrate that the proposed algorithm outperforms the state-of-the-art remarkably for finding risk bounded low-cost ...

Deep learning methods are proposed to apply to the sampling-based planner, developing a novel risk bounded near-optimal path planning algorithm named neural ...

The initial paths are often of poor quality. Therefore, we propose the NR-RRT algorithm to rapidly find near-optimal solutions with guaranteed bounded risk. It ...

NR-RRT: Neural risk-aware near-optimal path planning in uncertain nonconvex environments ... Reciprocally rotating magnetic actuation and automatic trajectory ...

NR-RRT: Neural Risk-Aware Near-Optimal Path Planning in Uncertain Nonconvex Environments ... path planning algorithm named neural risk-aware RRT (NR-RRT).

Many risk-aware path planners have been developed to explicitly limit the probability of collision to an acceptable bound in uncertain environments. However, ...

This paper presents a novel image-based path planning algorithm designed to take the environment map as the input without other preprocessing works and ...

Feb 17, 2021 · Abstract. This study develops a novel sampling-based path planning approach, simultaneously achieving uncertainty reduction of.