Hexagon-Based q-learning for object search with multiple robots

Authors:
Han-Ul Yoon;Kwee-Bo Sim
Affiliations:
School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea;School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Year:
2005

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Abstract

This paper presents the hexagon-based Q-leaning for object search with multiple robots. We set up an experimental environment with five small mobile robots, obstacles, and a target object. The robots were out to search for a target object while navigating in a hallway where some obstacles were placed. In this experiment, we used three control algorithms: a random search, an area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning to enhance the area-based action making process.