A coverage path planning approach for autonomous radiation mapping with a mobile robot. (16th August 2022)

• Record Type: Journal Article
• Authors: Abd Rahman, Nur Aira; Sahari, Khairul Salleh Mohamed; Hamid, Nasri A; Hou, Yew Cheong
• Is Part Of: International journal of advanced robotic systems. Volume 19:Number 4(2022)
• Publication Date: 2022-08-16
• Subjects: Field robotics -- coverage path planning -- radiation safety -- radiation mapping -- mobile robot navigation; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/17298806221116483
• Languages: English
• ISSNs: 1729-8806

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.