Learning-Based Risk-Bounded Path Planning Under Environmental Uncertainty

Building a general and efficient path planning framework in uncertain nonconvex environments is challenging due to the safety constraints and complex configuration. Traditional avenues usually involve convexifying obstacles and presume Gaussian distribution, which are not universal. Meanwhile, the f...

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Vydané v:	IEEE transactions on automation science and engineering Ročník 21; číslo 3; s. 4460 - 4470
Hlavní autori:	Meng, Fei, Chen, Liangliang, Ma, Han, Wang, Jiankun, Meng, Max Q.-H.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.07.2024
Predmet:	Collision avoidance deep learning methods Environmental factors Path planning Planning Probabilistic logic risk-bounded path planning Robots Sampling-based algorithm Three-dimensional displays Uncertainty
ISSN:	1545-5955, 1558-3783
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