Robust Autonomous Mobile Manipulation for Substation Inspection
Erik Pearson, Benjamin Mirisola, Cameron Murphy, Christine Huang, Connor O’Leary, Franklin Wong, Julia Meyerson, Luisa Bonfim, Matthew Zecca, N. Spina, Paul Szenher, Shalemuraju Katari, T Dohi, Thomas Colarusso, Thomas Gana, Brendan Englot
- Year
- 2024
- Citations
- 4
Abstract
Abstract The need for autonomous infrastructure inspections performed by mobile robots is becoming increasingly prevalent, to mitigate human error and inspect critical infrastructure with increased frequency, while reducing costs. Electric distribution substations contain a variety of high-power equipment that may occasionally fail, and we focus on inspecting pothead compartments as a representative test case. Frequent measurements of acoustic and transient earth voltage data can indicate degradation before failures occur. Handheld partial discharge (PD) sensors can gather these types of data. Measurements using PD sensors can be automated using a mobile manipulation platform with a custom end-effector. Accurate mapping, localization, and navigation are required to perform autonomous inspection tasks in indoor environments with unmanned ground vehicles. Computer vision and precise manipulator control are necessary for successful handheld sensor interactions. In this paper, we present and analyze a custom-integrated mobile manipulation system capable of performing these functions, which achieves a tradeoff between the small size needed to navigate through low-clearance areas, and the reach capabilities needed to collect the required measurements from pothead compartments.
Keywords
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