Tractor-trailer systems (TTSs) have been adopted in the logistics and transportation domain owing to their vast cargo capacity. Trajectory planning plays an important role in autonomous TTS driving, where existing predominant planners are usually based on graph search and sampling. However, such prevailing planners face the difficulties of poor real-time performance, due to the unique underactuated characteristic and complex kinematic constraints of TTS. Based on TTS motion characteristics and its application environment, this paper proposes a hybrid A* - jump point search (HA-JPS) planner, in which JPS improves the real-time performance, while hybrid A* provides the guarantee of kinematic constraints. Several TTS configures and typical environments were constructed to test the planning efficiency, trajectory feasibility, and completeness of HA-JPS. Comparative simulation experiment results illustrate that HA-JPS can improve real-time performance by more than 50% in different scenarios without loss of completeness.
An Environmental and Behavioral-oriented Search-based Trajectory Planning Approach for Tractor-trailer System in Narrow Environment
24.09.2023
2014068 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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