Sensor Devices and Systems for Robotics

  • Alícia Casals

Part of the NATO ASI Series book series (volume 52)

Table of contents

  1. Front Matter
    Pages I-IX
  2. Force and Torque Sensors

  3. Tactile Sensors

    1. Front Matter
      Pages 57-57
    2. J. B. C. Davies
      Pages 59-66
    3. A. Cameron, R. Daniel, H. Durrant-Whyte
      Pages 67-77
    4. P. W. Verbeek, P. T. A. Klaase, A. Theil
      Pages 79-88
    5. P. W. Verbeek
      Pages 89-89
  4. Acoustic Sensors

    1. Front Matter
      Pages 91-91
    2. J. S. Schoenwald
      Pages 93-109
    3. S. Monchaud
      Pages 111-126
    4. J. M. Martín, R. Ceres, J. No, L. Calderón
      Pages 143-156
  5. Optical Sensors

    1. Front Matter
      Pages 157-157
    2. Antonio B. Martínez, Vicenç Llario
      Pages 167-185
    3. P. Levi, L. Vajtá
      Pages 187-194
    4. O. D. Faugueras, G. Toscani
      Pages 195-213
  6. Other Kind of Sensors

    1. Front Matter
      Pages 241-241
    2. D. G. Whitehead, I. M. Bell, D. J. Mulvaney, A. Pugh, P. Sweeting
      Pages 243-251
  7. Applications

  8. Back Matter
    Pages 359-365

About these proceedings


As robots improve in efficiency and intelligence, there is a growing need to develop more efficient, accurate and powerful sensors in accordance with the tasks to be robotized. This has led to a great increase in the study and development of different kinds of sensor devices and perception systems over the last ten years. Applications that differ from the industrial ones are often more demanding in sensorics since the environment is not usually so well structured. Spatial and agricultural applications are examples of situations where the environment is unknown or variable. Therefore, the work to be done by a robot cannot be strictly programmed and there must be an interactive communication with the environment. It cannot be denied that evolution and development in robotics are closely related to the advances made in sensorics. The first vision and force sensors utilizing discrete components resulted in a very low resolution and poor accuracy. However, progress in VLSI, imaging devices and other technologies have led to the development of more efficient sensor and perception systems which are able to supply the necessary data to robots.


Normal artificial intelligence cognition control feedback learning modeling robot robotics sensor sensors signal processing

Editors and affiliations

  • Alícia Casals
    • 1
  1. 1.Facultat d’Informàtica de Barcelona (U.P.C.)BarcelonaSpain

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 1989
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-74569-0
  • Online ISBN 978-3-642-74567-6
  • Buy this book on publisher's site