Waalbot II: Adhesion Recovery and Improved Performance of a Climbing Robot using Fibrillar Adhesives

  • Authors:

  • Michael P. Murphy;Casey Kute;Yiğit Mengüç;Metin Sitti

  • Affiliations:

  • NanoRobotics Laboratory, Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, USA;NanoRobotics Laboratory, Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, USA;NanoRobotics Laboratory, Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, USA;NanoRobotics Laboratory, Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, USA

  • Venue:
  • International Journal of Robotics Research
  • Year:
  • 2011

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Abstract

This paper presents the design and optimization of a wall-climbing robot along with the incorporation of autonomous adhesion recovery and a motion planning implementation. The result is Waalbot II, an untethered 85 g robot able to climb on smooth vertical surfaces with up to a 100 g payload (117% body mass) or, when unburdened, on planar surfaces of any orientation at speeds up to 5 cm/s. Bio-inspired climbing mechanisms, such as Waalbot IIâ聙聶s gecko-like fibrillar adhesives, passive peeling, and force sensing, improve the overall climbing capabilities compared with initial versions, resulting in the ability to climb on non-smooth surfaces as well as on inverted smooth surfaces. Robot length scale optimization reveals and quantifies trends in the theoretical factor of safety and payload carrying capabilities. Autonomous adhesion recovery behavior provides additional climbing robustness without additional mechanical complexity to mitigate degradation and contamination. An implementation of a motion planner, designed to take into account Waalbot IIâ聙聶s kinematic constraints, results in the ability to navigate to a goal in complex three-dimensional environments while properly planning plane-to-plane transitions and avoiding obstacles. Experiments verified the improved climbing capabilities of Waalbot II as well as its novel semi-autonomous adhesion recovery behavior and motion planning.