David B. D'Ambrosio, Skyler Goodell, Joel Lehman, Sebastian Risi, and Kenneth O. Stanley (2012)
Multirobot Behavior Synchronization through Direct Neural Network Communication
In: Proceedings of the 5th International Conference on Intelligent Robotics and Applications (ICIRA-2012). New York, NY: Springer-Verlag, 2012 (12 pages).
Best Paper Award Finalist at ICIRA 2012
Note: This paper is accompanied with a set of video demos at http://eplex.cs.ucf.edu/demos/hive-brain-patrol.
The final publication is available at http://link.springer.com/chapter/10.1007/978-3-642-33515-0_59.
Abstract
Many important real-world problems, such as patrol or search and rescue, could benefit from the ability to train teams of robots to coordinate. One major challenge to achieving such coordination is determining the best way for robots on such teams to communicate with each other. Typical approaches employ hand-designed communication schemes that often require significant effort to engineer. In contrast, this paper presents a new communication scheme called the hive brain, in which the neural network controller of each robot is directly connected to internal nodes of other robots and the weights of these connections are evolved. In this way, the robots can evolve their own internal "language" to speak directly brain-to-brain. This approach is tested in a multirobot patrol synchronization domain where it produces robot controllers that synchronize through communication alone in both simulation and real robots, and that are robust to perturbation and changes in team size.