Rapid Coverage of Regions of Interest for Environmental Monitoring

Pinkam, Nantawat; Newaz, Abdullah Al Redwan; Jeong, Sungmoon; Chong, Nak Young

doi:10.1007/978-3-319-78452-6_17

Cited by 3 publications

(4 citation statements)

References 14 publications

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“…Moreover, segmentation of complex ROI would allow efficient coverage during the operation. Pinkam et al 49 proposed two adaptive area decomposition techniques to reduce the complexity of UAV large-scale explorations, namely recursive quadratic subdivision and Voronoi subdivision. In more general research, Goel et al 50 proposed rectangular boundaries within the current workspace to systematically cover an unknown environment, where the box is moved horizontally and vertically until the whole environment is covered.…”

Section: Related Workmentioning

confidence: 99%

“…Lazna et al 13 interpolated the discrete data points from CPP with Delaunay interpolation. Pinkam et al 49 established hotspots boundary lines by tracking continuous contaminated cells and estimated the best fit to an ellipse shape by least-squares criterion. Bird et al 33 proposed an exclusion zone to prevent cross-contamination by blocking the hotspot area as a physical obstacle in the occupancy map.…”

Section: Related Workmentioning

confidence: 99%

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

Rahman

Sahari

Hamid

et al. 2022

International Journal of Advanced Robotic Systems

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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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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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

Rahman

Sahari

Hamid

et al. 2022

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

show abstract

“…However, it did not consider the degradation of sensors due to presence of radiation. In an another work [9], agent tried to monitor an environment with unknown intensity of extreme environmental conditions. It translated the problem to a multiple target visiting problem.…”

Section: Related Workmentioning

confidence: 99%

“…The development of agents which can survey sites has revolutionized the field of surveillance and inspection. The recent [9] agent based fixed altitude CPP problem mapped the environment monitoring problem as a multiple target visiting problem. The multiple targets visiting problem was then formulated as Travelling Salesman Problem (TSP) [10].…”

Section: Introductionmentioning

confidence: 99%