Experimental Evaluation of Nearest Neighbor Exploration Approach in Field Environments

Publication Type:
Journal Article
IEEE Transactions on Automation Science and Engineering, 2017, 14 (2), pp. 869 - 880
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© 2017 IEEE. Inspecting surface conditions in 3-D environments such as steel bridges is a complex, time-consuming, and often hazardous undertaking that is an essential part of tasks such as bridge maintenance. Developing an autonomous exploration strategy for a mobile climbing robot would allow for such tasks to be completed more quickly and more safely than is possible with human inspectors. The exploration strategy tested in this paper, called the nearest neighbors exploration approach (NNEA), aims to reduce the overall exploration time by reducing the number of sensor position evaluations that need to be performed. NNEA achieves this by first considering at each time step only a small set of poses near to the current robot as candidates for the next best view. This approach is compared with another exploration strategy for similar robots performing the same task. The improvements between the new and previous strategy are demonstrated through trials on a test rig, and also in field trials on a ferromagnetic bridge structure. Note to Practitioners-This paper was motivated by the problem of inspecting confined spaces for rust and flaking paint with a manipulator robot arm. Existing approaches involve creating a large set of candidate robot poses to take a scan from. Evaluating all these candidate poses is very time consuming if full coverage is guaranteed. This paper suggests a principled method for restricting the size of this set in a way that does not reduce inspection coverage but decreases overall time taken for inspection.
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