Control Model Learning for Whole-Body Mobile Manipulation
Abstract
The ability to discover the effects of actions and apply this knowledge during goal-oriented action selection is a fundamental requirement of embodied intelligent agents. In our ongoing work, we hope to demonstrate the utility of learned control models for whole-body mobile manipulation. In this short paper we discuss preliminary work on learning a forward model of the dynamics of a balancing robot exploring simple arm movements. This model is then used to construct whole-body control strategies for regulating state variables using arm motion.
Cite
Text
Kuindersma. "Control Model Learning for Whole-Body Mobile Manipulation." AAAI Conference on Artificial Intelligence, 2010. doi:10.1609/AAAI.V24I1.7775Markdown
[Kuindersma. "Control Model Learning for Whole-Body Mobile Manipulation." AAAI Conference on Artificial Intelligence, 2010.](https://mlanthology.org/aaai/2010/kuindersma2010aaai-control/) doi:10.1609/AAAI.V24I1.7775BibTeX
@inproceedings{kuindersma2010aaai-control,
title = {{Control Model Learning for Whole-Body Mobile Manipulation}},
author = {Kuindersma, Scott},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2010},
pages = {1939-1940},
doi = {10.1609/AAAI.V24I1.7775},
url = {https://mlanthology.org/aaai/2010/kuindersma2010aaai-control/}
}