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Dextrous Robot Hands

  • Book
  • © 1990

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Table of contents (13 chapters)

  1. Lessons Learned from Human Hand Studies

  2. Dextrous Hand Control Architectures

  3. Lessons Learned from Dextrous Robot Hands

  4. Panel Discussion

Keywords

About this book

Manipulation using dextrous robot hands has been an exciting yet frustrating research topic for the last several years. While significant progress has occurred in the design, construction, and low level control of robotic hands, researchers are up against fundamental problems in developing algorithms for real-time computations in multi-sensory processing and motor control. The aim of this book is to explore parallels in sensorimotor integration in dextrous robot and human hands, addressing the basic question of how the next generation of dextrous hands should evolve. By bringing together experimental psychologists, kinesiologists, computer scientists, electrical engineers, and mechanical engineers, the book covers topics that range from human hand usage in prehension and exploration, to the design and use of robotic sensors and multi-fingered hands, and to control and computational architectures for dextrous hand usage. While the ultimate goal of capturing human hand versatility remains elusive, this book makes an important contribution to the design and control of future dextrous robot hands through a simple underlying message: a topic as complex as dextrous manipulation would best be addressed by collaborative, interdisciplinary research, combining high level and low level views, drawing parallels between human studies and analytic approaches, and integrating sensory data with motor commands. As seen in this text, success has been made through the establishment of such collaborative efforts. The future will hold up to expectations only as researchers become aware of advances in parallel fields and as a common vocabulary emerges from integrated perceptions about manipulation.

Editors and Affiliations

  • Jet Propulsion Laboratory, Pasadena, USA

    Subramanian T. Venkataraman

  • Center for Neural Engineering, Department of Computer Science, University of Southern California, Los Angeles, USA

    Thea Iberall

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