Review of Autonomous Path Planning Algorithms for Mobile Robots

Mobile robots, including ground robots, underwater robots, and unmanned aerial vehicles, play an increasingly important role in people’s work and lives. Path planning and obstacle avoidance are the core technologies for achieving autonomy in mobile robots, and they will determine the application pro...

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Bibliographic Details
Published in:Drones (Basel) 2023-03, Vol.7 (3), p.211
Main Authors: Qin, Hongwei, Shao, Shiliang, Wang, Ting, Yu, Xiaotian, Jiang, Yi, Cao, Zonghan
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
autonomous underwater robot
Autonomy
Control systems
Drone aircraft
Heuristic
mobile robot
Mobile robots
multi-robot cooperative
Multiple robots
Obstacle avoidance
Path planning
Planning
Robot dynamics
Robots
Underwater robots
unmanned aerial robot
Unmanned aerial vehicles
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Summary:Mobile robots, including ground robots, underwater robots, and unmanned aerial vehicles, play an increasingly important role in people’s work and lives. Path planning and obstacle avoidance are the core technologies for achieving autonomy in mobile robots, and they will determine the application prospects of mobile robots. This paper introduces path planning and obstacle avoidance methods for mobile robots to provide a reference for researchers in this field. In addition, it comprehensively summarizes the recent progress and breakthroughs of mobile robots in the field of path planning and discusses future directions worthy of research in this field. We focus on the path planning algorithm of a mobile robot. We divide the path planning methods of mobile robots into the following categories: graph-based search, heuristic intelligence, local obstacle avoidance, artificial intelligence, sampling-based, planner-based, constraint problem satisfaction-based, and other algorithms. In addition, we review a path planning algorithm for multi-robot systems and different robots. We describe the basic principles of each method and highlight the most relevant studies. We also provide an in-depth discussion and comparison of path planning algorithms. Finally, we propose potential research directions in this field that are worth studying in the future.
ISSN:2504-446X
2504-446X
DOI:10.3390/drones7030211