Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Utilizing object-object and object-scene context when planning to find things
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Coupled semi-supervised learning for information extraction
Proceedings of the third ACM international conference on Web search and data mining
An effective personal mobile robot agent through symbiotic human-robot interaction
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
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This paper describes an algorithm that enables a mobile robot to find an arbitrary object and take it to a destination location. Previous approaches have been able to search for a fixed set of objects. In contrast, our approach is able to dynamically construct a cost function to find any object by querying the web. The performance of our approach has been evaluated in a realistic simulator, and has been demonstrated on a companion robot, which can successfully execute plans such as finding a "coffee" and taking it to a destination location like, "Gates-Hillman Center, Room 7002."