English

Grounding Perception: A Developmental Approach to Sensorimotor Contingencies

Machine Learning 2018-10-05 v1 Artificial Intelligence Robotics Machine Learning

Abstract

Sensorimotor contingency theory offers a promising account of the nature of perception, a topic rarely addressed in the robotics community. We propose a developmental framework to address the problem of the autonomous acquisition of sensorimotor contingencies by a naive robot. While exploring the world, the robot internally encodes contingencies as predictive models that capture the structure they imply in its sensorimotor experience. Three preliminary applications are presented to illustrate our approach to the acquisition of perceptive abilities: discovering the environment, discovering objects, and discovering a visual field.

Keywords

Cite

@article{arxiv.1810.01870,
  title  = {Grounding Perception: A Developmental Approach to Sensorimotor Contingencies},
  author = {Alban Laflaquière and Nikolas Hemion and Michaël Garcia Ortiz and Jean-Christophe Baillie},
  journal= {arXiv preprint arXiv:1810.01870},
  year   = {2018}
}

Comments

8 pages, 4 figures, workshop at IROS 2015 conference

R2 v1 2026-06-23T04:27:35.946Z