无人机污染源自主搜寻算法综述

Autonomous search plays an important role in a wide range of applications, such as environmental protection, industrial monitoring, and search and rescue. Sensor platforms based on unmanned aerial vehicles (UAVs) have been regarded as one of the most efficient methods for achieving fully autonomous searching because of their superior flexibility and motility. This paper reviews existing algorithms for two important subjects, i.e., source seeking and boundary tracking, based on which their design principles are revealed. Although control-oriented and information-driven approaches are the two mainstream state-of-the-art methods for source seeking, their hybrids have been poorly studied. Regarding boundary tracking, existing solutions can be allocated into two classes: single-agent tracking and multiagent cooperative tracking. From the perspective of dual control for exploration and exploitation, this review outlines the fundamental insights into algorithm design and presents several visions for future research.