Abstract
In this paper we study online gait opti-
mization for modular robots. The learning strategy
we apply is distributed, independent on robot mor-
phology, and easy to implement. First we demonstrate
how the strategy allows an ATRON robot to adapt to
faults and changes in its morphology and we study the
strategy’s scalability. Second we extend the strategy
to learn the parameters of gait-tables for ATRON
and M-TRAN robots.We conclude that the presented
strategy is effective for online learning of gaits for
most types of modular robots and that learning can
effectively be distributed by having independent pro-
cesses learning in parallel.
| Original language | English |
|---|---|
| Journal | I E E E International Conference on Robotics and Automation. Proceedings |
| Pages (from-to) | 2765-2770 |
| ISSN | 1050-4729 |
| DOIs | |
| Publication status | Published - 2010 |
| Externally published | Yes |
| Event | 2010 IEEE International Conference on Robotics and Automation - Anchorage, AK, United States Duration: 3 May 2010 → 8 May 2010 http://icra2010.grasp.upenn.edu/ |
Conference
| Conference | 2010 IEEE International Conference on Robotics and Automation |
|---|---|
| Country | United States |
| City | Anchorage, AK |
| Period | 03/05/2010 → 08/05/2010 |
| Internet address |
Cite this
Christensen, D. J., Schultz, U. P., & Stoy, K. (2010). A Distributed Strategy for Gait Adaptation in Modular Robots. I E E E International Conference on Robotics and Automation. Proceedings, 2765-2770. https://doi.org/10.1109/ROBOT.2010.5509942