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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.
List of contents
I. Sensor Fusion and Integration.- An Integrated Sensor System for Robots.- Robot Tactile Perception.- Uncertainty in Robot Sensing.- II. Vision Algorithms and Architectures.- Robotic Vision Knowledge System.- Algorithm for Visible Surface Pattern Generation - a Tool for 3D Object Recognition.- Knowledge-Based Robot Workstation: Supervisor Design.- Robot/Vision System Calibrations in Automated Assembly.- III. Neural Networks, Parallel Algorithms and Control Architectures.- A Unified Modeling of Neural Networks Architectures.- Practical Neural Computing for Robots: Prospects for Real-Time Operation.- Self-Organizing Neuromorphic Architecture for Manipulator Inverse Kinematics.- Robotics Vector Processor Architecture for Real-Time Control.- On the Parallel Algorithms for Robotic Computations.- Report on the Group Discussion about Neural Networks in Robotics.- List of Lecturers and Participants.
