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Titel:

Density Planner: Minimizing Collision Risk in Motion Planning with Dynamic Obstacles using Density-based Reachability

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Lützow, Laura; Meng, Yue; Armijos, Andres Chavez; Fan, Chuchu
Abstract:
Uncertainty is prevalent in robotics. Due to measurement noise and complex dynamics, we cannot estimate the exact system and environment state. Since conservative motion planners are not guaranteed to find a safe control strategy in a crowded, uncertain environment, we propose a density-based method. Our approach uses a neural network and the Liouville equation to learn the density evolution for a system with an uncertain initial state. We can plan for feasible and probably safe trajectories by...     »
Kongress- / Buchtitel:
2023 IEEE International Conference on Robotics and Automation (ICRA)
Verlag / Institution:
IEEE
Publikationsdatum:
29.05.2023
Jahr:
2023
Volltext / DOI:
doi:10.1109/icra48891.2023.10161378
Copyright Informationen:
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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