Accession Number:

ADA126361

Title:

Vision-Based Predictive Robotic Tracking of a Moving Target.

Descriptive Note:

Interim rept.,

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA ROBOTICS INST

Personal Author(s):

Report Date:

1982-01-01

Pagination or Media Count:

71.0

Abstract:

This work represents a more general approach to robotic system design than one based on predefined responses in a controlled environment. An implementing of a vision-based robotic tracking system is presented in which target trajectory predictions enable the robot to track and intercept a moving target. A host microcomputer receives target position information from a vision module, predicts the targets trajectory, and issues tracking commands to the robot controlled. Five predictive algorithms are derived for implementation in the system, including a Kalman and an augmented Kalman filter. The use of one-step as well as absolute and relative n-step predictions is investigated. The best predictor algorithm is presented, by which one of the five predictions is selected to be used as the robotic tracking command. Using data from experimental trials, predictor results are compared and robotic tracking performance and interception success are evaluated for the target both moving and after it comes to rest. Constraints limiting the applicability of this implementation are discussed and possible improvements and extensions suggested. Author

Subject Categories:

  • Theoretical Mathematics
  • Active and Passive Radar Detection and Equipment

Distribution Statement:

APPROVED FOR PUBLIC RELEASE