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Design, Modeling and Experimentation of a Biomimetic Wall-climbing Robot for Multiple Surfaces

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Wall-climbing robots can work on steep terrain and obtain environment information in three dimensions for human in real time, which can improve operation efficiency. However, traditional single-mode robots cannot ensure… Click to show full abstract

Wall-climbing robots can work on steep terrain and obtain environment information in three dimensions for human in real time, which can improve operation efficiency. However, traditional single-mode robots cannot ensure the stable attachment on complex wall surfaces. Inspired by the structure characteristics of flies and clingfishes, three bionic structures including the flexible spine wheel, the adhesive material and the adsorption system are proposed. Aiming at task requirements on multiple walls and based on the above three bionic structures, a wall-climbing robot with the composed mode of “grabbing+adhesion+adsorption” is presented via the law of mechanism configuration synthesis. Using static analysis, the safe attachment conditions for the robot on smooth and rough walls are that the adsorption force is 30 N or more. Based on Newton’s Euler and Lagrange formulas, the dynamic equations of the robot on vertical walls are established to deduce that the maximum theoretical torque of the driving motor is 1.43 N·m at a uniform speed. Finally, the prototype of the wall-climbing robot is manufactured and tested on the vertical lime wall, coarse sandpaper wall and acrylic ceiling wall. Meanwhile, experiment results imply that the average maximum moving speed and the corresponding load are 7.19 cm·s −1 and 0.8 kg on the vertical lime wall, 7.78 cm·s −1 and 0.6 kg on the coarse sandpaper wall, and 5.93 cm·s −1 and 0.2 kg on the acrylic ceiling wall respectively. These findings could provide practical reference for the robot’s application on walls.

Keywords: experimentation biomimetic; wall climbing; climbing robot; modeling experimentation; wall; design modeling

Journal Title: Journal of Bionic Engineering
Year Published: 2020

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