A framework for multi-robot coverage analysis of large and complex structures

Penglei Dai (), Mahdi Hassan (), Xuerong Sun (), Ming Zhang (), Zhengwei Bian () and Dikai Liu ()
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Penglei Dai: University of Technology Sydney
Mahdi Hassan: University of Technology Sydney
Xuerong Sun: China Merchants Heavy Industry (Jiangsu) Co., Ltd
Ming Zhang: China Merchants Heavy Industry (Jiangsu) Co., Ltd
Zhengwei Bian: China Merchants Heavy Industry (Jiangsu) Co., Ltd
Dikai Liu: University of Technology Sydney

Journal of Intelligent Manufacturing, 2022, vol. 33, issue 5, No 18, 1545-1560

Abstract: Abstract Coverage analysis is essential for many coverage tasks (e.g., robotic grit-blasting, painting, and surface cleaning) performed by Autonomous Industrial Robots (AIRs). Coverage analysis enables (1) the performance evaluation (e.g., coverage rate and operation efficiency) of AIRs for a coverage task, and (2) the configuration design of a multi-AIR system (e.g., decision on the number of AIRs to be used). Multi-AIR coverage analysis of large and complex structures involves addressing various problems. Thus, a framework is presented in this paper that incorporates various modules (e.g., AIR reachability, AIR base placement, collision avoidance, and area partitioning and allocation) for appropriately addressing the associated problems. The modules within the framework provide the flexibility of utilizing different methods and algorithms, depending on the requirements of the target application. The framework is tested and validated by extensive analyses of 10 different scenarios with up to 10 AIRs.

Keywords: Coverage analysis; Autonomous industrial robot; Multiple robots; System configuration design (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10845-021-01745-8

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