Sensor-Based Robots: Algorithms and Architectures

1. Front Matter

   Pages I-X

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2. Sensor Fusion and Integration

   1. Front Matter

      Pages 1-1

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   2. An Integrated Sensor System for Robots

      • Ulrich Rembold, Paul Levi

      Pages 3-24

   3. Robot Tactile Perception

      • G. Buttazzo, A. Bicchi, P. Dario

      Pages 25-40

   4. Uncertainty in Robot Sensing

      • E. Grant

      Pages 41-57

3. Vision Algorithms and Architectures

   1. Front Matter

      Pages 59-59

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   2. Robotic Vision Knowledge System

      • Andrew K. C. Wong

      Pages 61-92

   3. Algorithm for Visible Surface Pattern Generation — a Tool for 3D Object Recognition

      • J. Majumdar, P. Levi, U. Rembold

      Pages 93-106

   4. Knowledge-Based Robot Workstation: Supervisor Design

      • Robert B. Kelley

      Pages 107-128

   5. Robot/Vision System Calibrations in Automated Assembly

      • F. G. King, G. V. Puskorius, F. Yuan, R. C. Meier, V. Jeyabalan, L. A. Feldkamp

      Pages 129-142

4. Neural Networks, Parallel Algorithms and Control Architectures

   1. Front Matter

      Pages 143-143

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   2. A Unified Modeling of Neural Networks Architectures

      • S. Y. Rung, J. N. Hwang

      Pages 145-164

   3. Practical Neural Computing for Robots: Prospects for Real-Time Operation

      • I. Aleksander

      Pages 165-178

   4. Self-Organizing Neuromorphic Architecture for Manipulator Inverse Kinematics

      • Jacob Barhen, Sandeep Gulati

      Pages 179-202

   5. Robotics Vector Processor Architecture for Real-Time Control

      • David E. Orin, P. Sadayappan, Y. L. C. Ling, K. W. Olson

      Pages 203-238

   6. On The Parallel Algorithms for Robotic Computations

      • C. S. George Lee

      Pages 239-280

   7. Report on the Group Discussion about Neural Networks in Robotics

      • Carme Torras

      Pages 281-282

5. Back Matter

   Pages 283-290

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Most industrial robots today have little or no sensory capability. Feedback is limited to information about joint positions, combined with a few interlock and timing signals. These robots can function only in an environment where the objects to be manipulated are precisely located in the proper position for the robot to grasp (i. e. , in a structured environment). For many present industrial applications, this level of performance has been adequate. With the increasing demand for high performance sensor-based robot manipulators in assembly tasks, meeting this demand and challenge can only be achieved through the consideration of: 1) efficient acquisition and processing of intemaVextemal sensory information, 2) utilization and integration of sensory information from various sensors (tactile, force, and vision) to acquire knowledge in a changing environment, 3) exploitation of inherent robotic parallel algorithms and efficient VLSI architectures for robotic computations, and finally 4) system integration into a working and functioning robotic system. This is the intent of the Workshop on Sensor-Based Robots: Algorithms and Architectures - to study the fundamental research issues and problems associated with sensor-based robot manipulators and to propose approaches and solutions from various viewpoints in improving present day robot manipula­ tors in the areas of sensor fusion and integration, sensory information processing, and parallel algorithms and architectures for robotic computations.

• Robot control
• Robot manipulation
• Robotersteuerung
• Robotics
• Robotik
• Sensorsysteme
• algorithms
• control
• knowledge
• parallel Systeme
• parallel systems
• proving
• robot
• sensor
• sensors
• complexity
• Engineering Economics

• School of Electrical Engineering, Purdue University, West Lafayette, USA

  C. S. George Lee

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