Graduated Fidelity Lattices for Motion Planning under Uncertainty

Autor:	González-Sieira, Adrián, Mucientes, Manuel, Bugarín, Alberto
Rok vydání:	2019
Předmět:	Computer Science - Robotics Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	We present a novel approach for motion planning in mobile robotics under sensing and motion uncertainty based on state lattices with graduated fidelity. The probability of collision is reliably estimated considering the robot shape, and the fidelity adapts to the complexity of the environment, improving the planning efficiency while maintaining the performance. Safe and optimal paths are found with an informed search algorithm, for which a novel multi-resolution heuristic is presented. Results for different scenarios and robot shapes are given, showing the validity of the proposed methods. Comment: Text accepted for publication in the 2019 IEEE International Conference on Robotics and Automation (ICRA)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1905.13531 Zobrazit plný text záznamu View this record from Arxiv