计算机科学
人工智能
明星(博弈论)
情报检索
计算机视觉
数学
数学分析
作者
Yiming Luo,Zixuan Zhuang,Neng Pan,Feng Chen,Shaojie Shen,Fei Gao,Hui Cheng,Boyu Zhou
出处
期刊:IEEE robotics and automation letters
日期:2024-03-20
卷期号:9 (5): 4329-4336
被引量:2
标识
DOI:10.1109/lra.2024.3379840
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 1 .
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