Header logo is

Biomimetic smooth pursuit based on fast learning of the target dynamics

2001

Conference Paper

am


Following a moving target with a narrow-view foveal vision system is one of the essential oculomotor behaviors of humans and humanoids. This oculomotor behavior, called ``Smooth Pursuit'', requires accurate tracking control which cannot be achieved by a simple visual negative feedback controller due to the significant delays in visual information processing. In this paper, we present a biologically inspired and control theoretically sound smooth pursuit controller consisting of two cascaded subsystems. One is an inverse model controller for the oculomotor system, and the other is a learning controller for the dynamics of the visual target. The latter controller learns how to predict the target's motion in head coordinates such that tracking performance can be improved. We investigate our smooth pursuit system in simulations and experiments on a humanoid robot. By using a fast on-line statistical learning network, our humanoid oculomotor system is able to acquire high performance smooth pursuit after about 5 seconds of learning despite significant processing delays in the syste

Author(s): Shibata, T. and Schaal, S.
Book Title: IEEE International Conference on Intelligent Robots and Systems (IROS 2001)
Year: 2001

Department(s): Autonomous Motion
Bibtex Type: Conference Paper (inproceedings)

Cross Ref: p1461
Note: clmc
URL: http://www-clmc.usc.edu/publications/S/shibata-IROS2001.pdf

BibTex

@inproceedings{Shibata_IICIRS_2001,
  title = {Biomimetic smooth pursuit based on fast learning of the target dynamics},
  author = {Shibata, T. and Schaal, S.},
  booktitle = {IEEE International Conference on Intelligent Robots and Systems (IROS 2001)},
  year = {2001},
  note = {clmc},
  crossref = {p1461},
  url = {http://www-clmc.usc.edu/publications/S/shibata-IROS2001.pdf}
}