A coverage path planning approach for autonomous radiation mapping with a mobile robot

IF 2.3 4区 计算机科学 Q2 Computer Science International Journal of Advanced Robotic Systems Pub Date : 2022-07-01 DOI:10.1177/17298806221116483
Nur Aira Abd Rahman, K. Sahari, N. A. Hamid, Yew Cheong Hou
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引用次数: 7

Abstract

In nuclear and radiation-related industries, it is crucial to ensure that the radiation dose exposure to the radiation worker is maintained below the permissible dose limit. A radiation map is a useful tool for visualizing the radiation distribution across the work area and for coordinating activities involving the hotspots (high radiation areas). The goal of this work was to design and implement a coverage path planning approach for autonomous radiation mapping carried out by a mobile robot. Given a 2D occupancy map, a method to generate uniformly distributed sampling points was proposed. The geometry of the region of interest, the radiation detector module, and the radiation measurement parameters were considered in formulating the sampling positions. Next, the coverage path planning planner integrates the nearest neighbor and depth-first search algorithms to create a continuous path that enables the robot to visit all the sampling points. The K-means clustering algorithm is added for systematic coverage of a large number of sampling points. The clustering provides options to partition the region of interest into smaller spaces, where the robot would perform the mapping cluster by cluster. Finally, the method of building the radiation map from the acquired data was also presented. The approach was implemented in ROS using a commercial mobile robot equipped with a Geiger–Muller detector. The performance and reliability of the proposed approach were evaluated with a series of simulations and real-world experiments. The results showed that the robot is able to perform autonomous radiation mapping at various target areas. The accuracy of the generated radiation map and the hotspots classifications were also compared and evaluated with conventional manual measurements. Overall, the theoretical frameworks and experiments have provided convincing results in the automation of hazardous work and subsequently toward improving the occupational safety of radiation workers.
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移动机器人自主辐射地图覆盖路径规划方法
在核工业和辐射相关行业,至关重要的是要确保辐射工作者的辐射剂量暴露保持在允许的剂量限值以下。辐射图是一种有用的工具,用于可视化整个工作区域的辐射分布,并用于协调涉及热点(高辐射区域)的活动。这项工作的目标是设计和实现一种覆盖路径规划方法,用于由移动机器人进行的自主辐射测绘。在给定二维占用图的情况下,提出了一种生成均匀分布采样点的方法。在制定采样位置时,考虑了感兴趣区域的几何形状、辐射探测器模块和辐射测量参数。接下来,覆盖路径规划器集成了最近邻居和深度优先搜索算法,以创建一条连续路径,使机器人能够访问所有采样点。为了系统覆盖大量采样点,增加了K-means聚类算法。集群提供了将感兴趣区域划分为更小空间的选项,机器人将在其中逐集群执行映射。最后,还介绍了根据采集的数据建立辐射图的方法。该方法在ROS中使用配备盖革-穆勒检测器的商用移动机器人实现。通过一系列仿真和真实世界的实验对所提出的方法的性能和可靠性进行了评估。结果表明,该机器人能够在不同的目标区域进行自主辐射测绘。生成的辐射图和热点分类的准确性也与传统的手动测量进行了比较和评估。总的来说,理论框架和实验在危险工作的自动化以及随后提高辐射工作者的职业安全方面提供了令人信服的结果。
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来源期刊
CiteScore
6.50
自引率
0.00%
发文量
65
审稿时长
6 months
期刊介绍: International Journal of Advanced Robotic Systems (IJARS) is a JCR ranked, peer-reviewed open access journal covering the full spectrum of robotics research. The journal is addressed to both practicing professionals and researchers in the field of robotics and its specialty areas. IJARS features fourteen topic areas each headed by a Topic Editor-in-Chief, integrating all aspects of research in robotics under the journal''s domain.
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