Guided Sampling-Based Motion Planning with Dynamics in Unknown Environments

Sampling-based motion planning with dynamics remains challenging in unknown environments, where the planner must generate trajectories that are both collision-free and dynamically feasible without prior knowledge of the map. This paper develops a guided sampling-based motion-planning approach for a single robot with dynamics that biases the search toward promising regions of the state space, improving planning efficiency as the robot explores and reacts to a partially known environment.

Citation: Abhish Khanal, Hoang-Dung Bui, Gregory J. Stein, Erion Plaku (2023). "Guided Sampling-Based Motion Planning with Dynamics in Unknown Environments." CASE 2023. https://ieeexplore.ieee.org/abstract/document/10260357