Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
5-2013
Abstract
In robotics research, perception is one of the most challenging tasks. In contrast to existing approaches that rely only on computer vision, we propose an alternative method for improving perception by learning from human teammates. To evaluate, we apply this idea to a door detection problem. A set of preliminary experiments has been completed using software agents with real vision data. Our results demonstrate that information inferred from teammate observations significantly improves the perception precision.
Keywords
Robot perception, Robot-human hybrid teams
Discipline
Artificial Intelligence and Robotics
Research Areas
Data Science and Engineering; Intelligent Systems and Optimization
Publication
Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems, Saint Paul, Minnesota, 2013 May 6-10
Volume
2
First Page
1147
Last Page
1148
Publisher
International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
City or Country
Saint Paul, Minnesota
Citation
OH, Jean; SUPPE, Arne; STENTZ, Anthony; and HEBERT, Martial.
Enhancing robot perception using human teammates. (2013). Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems, Saint Paul, Minnesota, 2013 May 6-10. 2, 1147-1148.
Available at: https://ink.library.smu.edu.sg/sis_research/8233
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.