This paper presents an autonomous magnetic wheel-driven climbing robot for automatic inspection of above ground steel storage structures, particularly for large even vertical surfaces of above ground tall steel structures. The design, simulation and experimental investigations on a multi-layer permanent magnetic wheel mechanism are discussed. A Finite element model for magneto-static (FEMM) analysis is proposed for an optimal wheel mechanism design. Laboratory experiments have been performed to measure adhesion force generated by the developed magnetic wheel mechanism and compared with simulation results obtained by proposed finite element model. The effect of rubber grip thickness on magnetic wheel for measuring adhesion force is also studied. The coefficient of friction, which plays a vital role for robot locomotion, has been measured experimentally. It should be enough to provide sufficient traction by providing an extra rubber grip added around to the wheel rim. Analysis of forces due to magnetic wheel adhesion mechanism has been made for avoiding climbing robot slipping and toppling while crawling on vertical/incline wall. The wireless communication and control system for prototype climbing robot has been developed using ATMega microcontroller based Arduino boards, motor driver IC, XBee transceiver. The developed autonomous four-wheel differential drive magnetic climbing robot can be controlled remotely from a ground station up to 90 m outdoor line-of-sight working range. The prototype-climbing robot has demonstrated various maneuverability trials on a vertical ferrous surface, and described in this paper.
- Dynamic Systems and Control Division
Development of Magnetic Adhesion Based Wheel-Driven Climbing Machine for Ferrous Surface Applications
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Bisht, RS, Pathak, PM, & Panigrahi, SK. "Development of Magnetic Adhesion Based Wheel-Driven Climbing Machine for Ferrous Surface Applications." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 1: Advances in Control Design Methods; Advances in Nonlinear Control; Advances in Robotics; Assistive and Rehabilitation Robotics; Automotive Dynamics and Emerging Powertrain Technologies; Automotive Systems; Bio Engineering Applications; Bio-Mechatronics and Physical Human Robot Interaction; Biomedical and Neural Systems; Biomedical and Neural Systems Modeling, Diagnostics, and Healthcare. Atlanta, Georgia, USA. September 30–October 3, 2018. V001T04A016. ASME. https://doi.org/10.1115/DSCC2018-9181
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