Star-Searcher: A Complete and Efficient Aerial System for Autonomous Target Search in Complex Unknown Environments
IEEE Robotics and Automation Letters(2024)
摘要
This paper tackles the challenge of autonomous target search using unmanned
aerial vehicles (UAVs) in complex unknown environments. To fill the gap in
systematic approaches for this task, we introduce Star-Searcher, an aerial
system featuring specialized sensor suites, mapping, and planning modules to
optimize searching. Path planning challenges due to increased inspection
requirements are addressed through a hierarchical planner with a
visibility-based viewpoint clustering method. This simplifies planning by
breaking it into global and local sub-problems, ensuring efficient global and
local path coverage in real-time. Furthermore, our global path planning employs
a history-aware mechanism to reduce motion inconsistency from frequent map
changes, significantly enhancing search efficiency. We conduct comparisons with
state-of-the-art methods in both simulation and the real world, demonstrating
shorter flight paths, reduced time, and higher target search completeness. Our
approach will be open-sourced for community benefit at
https://github.com/SYSU-STAR/STAR-Searcher.
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关键词
Aerial Systems: Perception and Autonomy,Aerial Systems: Applications,Search and Rescue Robots
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