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Dual-stage Planner for Autonomous Radioactive Source Localization in Unknown Environments

ROBOTICS AND AUTONOMOUS SYSTEMS(2024)

Harbin Inst Technol | Carnegie Mellon Univ

Cited 0|Views15
Abstract
This paper describes a novel approach for the autonomous localization of radioactive sources in complex unknown environments. The approach contains two stages: a source tracking stage for detailed source term estimation (STE) with recent measurements, and a relocation stage for transiting the robot to another sub-area after the current one is ruled out. The STE algorithm in conjunction with the convex polyhedrons extracted from the environment enables our method to be deployed in realistic scenarios with complex obstacles, which are often unfeasible for existing methods. The source confirmation algorithm in the relocation stage considerably accelerates the overall processing, improving the time efficiency in finding the radioactive sources. In both simulations and experiments, this approach is able to precisely localize at the success rate of 90% within an average of less than 13 measurements in 7 different environments, which is impressive when compared to the traditional STE which can hardly achieve an accurate estimation in most cases.
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Key words
Source localization,Search and rescue robot,Reactive and sensor-based planner,Dual stage planner
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要点】:本文提出了一种双阶段规划器,用于在未知环境中自主定位放射性源,通过结合详细源项估计(STE)和机器人重定位策略,实现了高效率和精确的定位效果。

方法】:该方法分为两个阶段,首先是源跟踪阶段,利用最近测量数据来进行详细的源项估计,并使用从环境中提取的凸多边形来适应复杂障碍物场景;其次是重定位阶段,采用源确认算法加快处理速度,提高寻找放射性源的时间效率。

实验】:通过在7种不同环境的模拟和实验中验证,该方法平均在13次测量内以90%的成功率精确定位放射性源,相比传统STE方法在大多数情况下难以实现准确估计,显示出显著优势。实验使用的数据集为7种不同环境的模拟数据。