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Experimental Evaluation of Nearest Neighbor Exploration Approach in Field Environments

机译:野外环境中近邻探测方法的实验评估

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摘要

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.
机译:在3D环境(例如钢桥)中检查表面状况是一项复杂,耗时且通常很危险的工作,这是桥梁维护等任务的重要组成部分。为移动攀爬机器人开发自主探索策略,将使这些任务比人工检查员能够更快,更安全地完成。本文测试的探索策略称为最近邻居探索方法(NNEA),旨在通过减少需要执行的传感器位置评估次数来减少总体探索时间。 NNEA通过首先在每个时间步上考虑当前机器人附近的一小部分姿势作为下一个最佳视图的候选者,来实现这一目标。将此方法与执行相同任务的类似机器人的另一种探索策略进行了比较。通过在试验台上进行试验以及在铁磁桥结构上进行的现场试验,证明了新策略与先前策略之间的改进。

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