An Overview of Motion-Planning Algorithms for Autonomous Ground Vehicles with Various Applications
Ajitesh Gautam, Yuping He, Xianke Lin
Abstract
<div>With the rapid development and the growing deployment of autonomous ground vehicles (AGVs) worldwide, there is an increasing need to design reliable, efficient, robust, and scalable motion-planning algorithms. These algorithms are crucial for fulfilling the desired goals of safety, comfort, efficiency, and accessibility. To design optimal motion-planning algorithms, it is beneficial to explore existing techniques and make improvements by addressing the limitations of associated techniques, utilizing hybrid algorithms, or developing novel strategies. This article categorizes and overviews numerous motion-planning algorithms for AGVs, shedding light on their strengths and weaknesses for a comprehensive understanding. For various applications of AGVs, such as urban and off-road autonomous driving, the features of driving conditions and vehicle kinodynamics are outlined, and sample-tailored motion-planning algorithms built upon relevant canonical techniques are briefly introduced. As a result of the overview, future research efforts on motion-planning techniques are identified and discussed.</div>