DP-A: For Path Planing of UGV and Contactless Delivery

The unmanned logistics and distribution urgently require a large number of unmanned ground vehicles(UGVs) under the influence of the potential spread of the Coronavirus Disease 2019 (COVID-19). The path planning of UGV relies excessively on SLAM map, and has no self-optimization and learning ability...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems 2024-01, Vol.25 (1), p.907-919
Hauptverfasser:	Gan, Xingli, Huo, Zhihui, Li, Wei
Format:	Artikel
Sprache:	eng
Schlagworte:	A-Star Algorithms Autonomous vehicles Barriers Changing environments Classification algorithms Collision avoidance contactless delivery Coronaviruses COVID-19 Heuristic algorithms Logistics Machine learning Optimization Path planning Planing Planning Q-learning Reinforcement learning robotics Robots Unmanned ground vehicles unmanned logistics Viral diseases
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