Sensor Devices and Systems for Robotics

1. Front Matter

   Pages I-IX

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2. Force and Torque Sensors

   1. Front Matter

      Pages 1-1

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   2. Joint Force Sensing for Unified Motor Learning

      • A. Mukerjee

      Pages 3-15

   3. Modelling the Interaction between Robot and Environment

      • A. A. Goldenberg

      Pages 17-36

   4. Pneumatic Sensors: Their Use and Performance in Force, Tactile and Position Sensing and in Shape Recognition

      • A. Romiti

      Pages 37-55

3. Tactile Sensors

   1. Front Matter

      Pages 57-57

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   2. Carbon Fibre Sensors

      • J. B. C. Davies

      Pages 59-66

   3. Tactile Geometry for Images and Normals

      • A. Cameron, R. Daniel, H. Durrant-Whyte

      Pages 67-77

   4. A Video Speed Tactile Camera

      • P. W. Verbeek, P. T. A. Klaase, A. Theil

      Pages 79-88

   5. Present and Future of Tactile Sensors

      • P. W. Verbeek

      Pages 89-89

4. Acoustic Sensors

   1. Front Matter

      Pages 91-91

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   2. Acoustic Range Sensing for Robotic Control

      • J. S. Schoenwald

      Pages 93-109

   3. SONAIR Ultrasonic Range Finders

      • S. Monchaud

      Pages 111-126

   4. Ultrasonic Imaging for Industrial Scene Analysis

      • H. Urban

      Pages 127-141

   5. Adaptative Ultrasonic Range-Finder for Robotics

      • J. M. Martín, R. Ceres, J. No, L. Calderón

      Pages 143-156

5. Optical Sensors

   1. Front Matter

      Pages 157-157

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   2. TH 7864 Area Array Charge-Coupled Device (CCD) Image Sensor with Built-In Antiblooming Device

      • D. Herault, G. Boucharlat

      Pages 159-165

   3. Real Time Holes Location. A Step Forward in Bin Picking Tasks

      • Antonio B. Martínez, Vicenç Llario

      Pages 167-185

   4. Combined 2-D and 3-D Robot Vision System

      • P. Levi, L. Vajtá

      Pages 187-194

   5. The Calibration Problem for Stereoscopic Vision

      • O. D. Faugueras, G. Toscani

      Pages 195-213

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
• complexity

• Facultat d’Informàtica de Barcelona (U.P.C.), Barcelona, Spain

  Alícia Casals

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