Tackling Existence Probabilities of Objects with Motion Planning for Automated Urban Driving

Autor:	Tas, Omer Sahin, Stiller, Christoph
Rok vydání:	2020
Předmět:	Computer Science - Robotics
Druh dokumentu:	Working Paper
Popis:	Motion planners take uncertain information about the environment as an input. The environment information is often quite noisy and has a tendency to contain false positive object detection. State-of-the-art motion planners consider all objects alike, thus producing overcautious behavior. In this paper we present a planning approach that considers alternative maneuvers in a combined fashion and plans a motion that is formed by the probabilities of those alternatives. The proposed planner can smoothly react to objects with low existence probability while remaining collision-free in case their existence substantiates. In this way, it tolerates the faults arising from perception and prediction, thus reducing their impact on operational reliability. Comment: 5 pages, 5 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2002.01254 Zobrazit plný text záznamu View this record from Arxiv