A survey on fused path planning for mobile robots: improved A* and timed-elastic band (TEB) algorithms
TL;DR
A comprehensive synthesis is provided, followed by the identification of several frontier research directions from the perspective of algorithmic architectural evolution, including tightly coupled optimization modeling, uncertainty-driven adaptive fusion, semantic perception augmentation, and distributed expansion for multi-robot systems.
Abstract
Path planning stands as a pivotal technology within the realm of autonomous mobile robots. In recent years, hierarchical architectures that integrate global and local planning have emerged as a prominent research paradigm. This paper focuses on the synergistic fusion of the improved A* global planner and the Timed Elastic Band (TEB) local planner, providing a systematic review of state-of-the-art research progress. Initially, the optimization strategies/methodologies and technical attributes of both the improved A* and TEB algorithms are elucidated. Subsequently, the discourse shifts to an in-depth analysis of the design philosophy, collaborative mechanisms, and representative application scenarios of the A*-TEB hybrid framework. Finally, a comprehensive synthesis is provided, followed by the identification of several frontier research directions from the perspective of algorithmic architectural evolution, including tightly coupled optimization modeling, uncertainty-driven adaptive fusion, semantic perception augmentation, and distributed expansion for multi-robot systems.