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Proceedings Paper

Real Time Target Tracking Using Dedicated Vision Hardware
Author(s): Keith Kambies; Peter Walsh
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Paper Abstract

This paper describes a real-time vision target tracking system developed by Adaptive Automation, Inc. and delivered to NASA's Launch Equipment Test Facility, Kennedy Space Center, Florida. The target tracking system is part of the Robotic Application Development Laboratory (RADL) which was designed to provide NASA with a general purpose robotic research and development test bed for the integration of robot and sensor systems. One of the first RADL system applications is the closing of a position control loop around a six-axis articulated arm industrial robot using a camera and dedicated vision processor as the input sensor so that the robot can locate and track a moving target. The vision system is inside of the loop closure of the robot tracking system, therefore, tight throughput and latency constraints are imposed on the vision system that can only be met with specialized hardware and a concurrent approach to the processing algorithms. State of the art VME based vision boards capable of processing the image at frame rates were used with a real-time, multi-tasking operating system to achieve the performance required. This paper describes the high speed vision based tracking task, the system throughput requirements, the use of dedicated vision hardware architecture, and the implementation design details. Important to the overall philosophy of the complete system was the hierarchical and modular approach applied to all aspects of the system, hardware and software alike, so there is special emphasis placed on this topic in the paper.

Paper Details

Date Published: 22 March 1988
PDF: 7 pages
Proc. SPIE 0849, Automated Inspection and High-Speed Vision Architectures, (22 March 1988); doi: 10.1117/12.942839
Show Author Affiliations
Keith Kambies, Adaptive Automation, Inc. (United States)
Peter Walsh, Adaptive Automation, Inc. (United States)

Published in SPIE Proceedings Vol. 0849:
Automated Inspection and High-Speed Vision Architectures
Rolf-Juergen Ahlers; Michael J. W. Chen, Editor(s)

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