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The research of robots to assist people in inspecting the quality of steel bridges has attracted significant attention in recent years. However, the intricate structure of the steel bridge components poses a massive challenge for researchers to move the robot across the bridge to perform the tests. This paper presents a new development of a hybrid flying-climbing robotic system, which can move flexibly and quickly to different positions on the steel bridge. In addition to using high-resolution cameras for an overview, the design allows the robot to stick to steel surfaces and act as a mobile robot for more detailed inspection with our developed giant magneto-resistance (GMR) sensor array system. We conduct a mechanical analysis to show the climbing capability of the mobile part. Additionally, we develop a landing algorithm to allow the robot to land on a steel surface to perform in-depth inspection safely. The designed GMR sensor array has shown the capability of detecting steel cracks to support the in-depth inspection mode. We have tested and validated our developed robot on real bridges to ensure that the design works well and is stable.
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Strategic Sacrifice: Self-Organized Robot Swarm Localization for Inspection Productivity
Robot swarms offer significant potential for inspecting di- verse infrastructure, ranging from bridges to space stations. However, effective inspection requires accurate robot localization, which demands substantial computational resources and limits productivity. Inspired by biological systems, we introduce a novel cooperative localization mech- anism that minimizes collective computation expenditure through self- organized sacrifice. Here, a few agents bear the computational burden of localization; through local interactions, they improve the inspection pro- ductivity of the swarm. Our approach adaptively maximizes inspection productivity for unconstrained trajectories in dynamic interaction and environmental settings. We demonstrate the optimality and robustness using mean-field analytical models, multi-agent simulations, and hard- ware experiments with metal climbing robots inspecting a 3D cylinder.
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- Award ID(s):
- 2240407
- PAR ID:
- 10613102
- Publisher / Repository:
- 17th International Symposium on Distributed Autonomous Robotic Systems (DARS'24) ; Springer Advanced Proceedings in Robotics (SPAR)
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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