By Topic

Real-time identification and predictive control of fast mobile robots using global vision sensing

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Sen Gupta, G. ; Inst. of Inf. Sci. & Technol., Massey Univ., New Zealand ; Messom, C.H. ; Demidenko, S.

This paper presents a predictive controller for intercepting mobile targets. A global vision system is used to identify fast moving objects and uses a color threshold technique to calculate their position and orientation. The inherent systemic noise in the raw sensor data, as well as vision quantization noise, is smoothed using Kalman filtering before being fed to the controller, and it is shown that this leads to superior accuracy of the controller. The predictive controller is based on the state transition-based control (STBC) technique. As a case study, STBC has been applied to a goalkeeper's behavior in robot soccer which includes interception and clearance of ball. Further evaluation of the controller has been done for shooting the ball toward a target position. The system is examined for both stationary and moving objects. It is shown that predictive filtering of rough sensor data is essential to increase the reliability and accuracy of detection, and thus interception, of fast moving objects.

Published in:

Instrumentation and Measurement, IEEE Transactions on  (Volume:54 ,  Issue: 1 )