Model Structuring and Concept Recognition: Two Aspects of Learning for a Mobile Robot
Abstract
We present here a method for providing a mobile robot with learning capabilities. The method is based on a model of the environment with several hierarchical levels organized by degree of abstraction. The mathematical structuring tool used is the decomposition of a graph into its k-connected components (k=2 and k=3). This structure allows the robot to improve navigation procedures and to recognize some concepts, such as a door, a room, or a corridor.
Cite
Text
Laumond. "Model Structuring and Concept Recognition: Two Aspects of Learning for a Mobile Robot." International Joint Conference on Artificial Intelligence, 1983.Markdown
[Laumond. "Model Structuring and Concept Recognition: Two Aspects of Learning for a Mobile Robot." International Joint Conference on Artificial Intelligence, 1983.](https://mlanthology.org/ijcai/1983/laumond1983ijcai-model/)BibTeX
@inproceedings{laumond1983ijcai-model,
title = {{Model Structuring and Concept Recognition: Two Aspects of Learning for a Mobile Robot}},
author = {Laumond, Jean-Paul},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1983},
pages = {839-841},
url = {https://mlanthology.org/ijcai/1983/laumond1983ijcai-model/}
}