Contact sensing and grasping performance of compliant hands

  • Authors:

  • Aaron M. Dollar;Leif P. Jentoft;Jason H. Gao;Robert D. Howe

  • Affiliations:

  • Yale School of Engineering and Applied Science, Yale University, New Haven, USA 06510;Harvard School of Engineering and Applied Sciences, Harvard University, Cambridge, USA 02138;Harvard School of Engineering and Applied Sciences, Harvard University, Cambridge, USA 02138;Harvard School of Engineering and Applied Sciences, Harvard University, Cambridge, USA 02138

  • Venue:
  • Autonomous Robots
  • Year:
  • 2010

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Abstract

Limitations in modern sensing technologies result in large errors in sensed target object geometry and location in unstructured environments. As a result, positioning a robotic end-effector includes inherent error that will often lead to unsuccessful grasps. In previous work, we demonstrated that optimized configuration, compliance, viscosity, and adaptability in the mechanical structure of a robot hand facilitates reliable grasping in unstructured environments, even with purely feedforward control of the hand. In this paper we describe the addition of a simple contact sensor to the fingerpads of the SDM Hand (Shape Deposition Manufactured Hand), which, along with a basic control algorithm, significantly expands the grasp space of the hand and reduces contact forces during the acquisition phase of the grasp. The combination of the passive mechanics of the SDM Hand along with this basic sensor suite enables positioning errors of over 5 cm in any direction. In the context of mobile manipulation, the performance demonstrated here may reduce the need for much of the complex array of sensing currently utilized on mobile platforms, greatly increase reliability, and speed task execution, which can often be prohibitively slow.