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Versatile robotic platform for structural health monitoring and surveillance

  • Esser, Brian (Department of Mechanical Engineering, University of Vermont) ;
  • Huston, Dryver R. (Department of Mechanical Engineering, University of Vermont)
  • 투고 : 2004.06.01
  • 심사 : 2005.09.20
  • 발행 : 2005.10.25

초록

Utilizing robotic based reconfigurable nodal structural health monitoring systems has many advantages over static or human positioned sensor systems. However, creating a robot capable of traversing a variety of civil infrastructures is a difficult task, as these structures each have unique features and characteristics posing a variety of challenges to the robot design. This paper outlines the design and implementation of a novel robotic platform for deployment on ferromagnetic structures as an enabling structural health monitoring technology. The key feature of this design is the utilization of an attachment device which is an advancement of the common magnetic base found in the machine tool industry. By mechanizing this switchable magnetic circuit and redesigning it for light weight and compactness, it becomes an extremely efficient and robust means of attachment for use in various robotic and structural health monitoring applications. The ability to engage and disengage the magnet as needed, the very low power required to do so, the variety of applicable geometric configurations, and the ability to hold indefinitely once engaged make this device ideally suited for numerous robotic and distributed sensor network applications. Presented here are examples of the mechanized variable force magnets, as well as a prototype robot which has been successfully deployed on a large construction site. Also presented are other applications and future directions of this technology.

키워드

참고문헌

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  1. Peristaltic Wave Locomotion and Shape Morphing with a Millipede Inspired System vol.27, pp.4, 2017, https://doi.org/10.1007/s00332-017-9372-7
  2. Path Following and Shape Morphing With a Continuous Slender Mechanism vol.137, pp.10, 2015, https://doi.org/10.1115/1.4030816
  3. Autonomous vision-based damage chronology for spatiotemporal condition assessment of civil infrastructure using unmanned aerial vehicle vol.25, pp.6, 2005, https://doi.org/10.12989/sss.2020.25.6.733