By Topic

Evolving Motion-tracking Behaviour For a Panning Camera Head

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
$15 $15
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

4 Author(s)

This paper details experiments in which neural network controllers were evolved in simulation that allowed a simple panning camera head to track patterned objects moving against similarly patterned backgrounds in reality. It begins with a discussion of minimal simulations: fast-running, easy-to-build simulations for the evolution of real robot controllers (Jakobi, 1998a; Jakobi, 1998b). The minimeli simulation with which the motion-tracking controllers were evolved (along with the rest of the evolutionary machinery) is then described. Experimental results axe offered in which an evolved controller was downloaded onto a simple panning camera head and satisfactorily tracked two very differently patterned objects as they moved against similarly patterned backgrounds in a random fashion.