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Experimental Evaluation of Nearest Neighbor Exploration Approach in Field Environments

Phillip Quin, Gavin Paul, Dikai Liu

Year
2017
Citations
12

Abstract

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.

Keywords

Bridge (graph theory)RobotTask (project management)Mobile robotComputer scienceSet (abstract data type)Field (mathematics)Artificial intelligencek-nearest neighbors algorithmEngineering

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