PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Human Heuristics for a Team of Mobile Robots
Charles Tijus, Nicolas Bredeche, Yves Kodratoff, Mary Felkin, Cedric Hartland, Elisabetta Zibetti and Vincent Besson
In: the 5th IEEE International Conference on Research, Innovation and Vision for the Future (RIVF'07), March 2007, Hanoi, Vietnam.


This paper is at the crossroad of Cognitive Psychology and AI Robotics. It reports a cross-disciplinary project concerned about implementing human heuristics within autonomous mobile robots. In the following, we address the problem of relying on human-based heuristics to endow a group of mobile robots with the ability to solve problems such as target finding in a labyrinth. Such heuristics may provide an efficient way to explore the environment and to decompose a complex problem into subtasks for which specific heuristics are efficient. We first present a set of experiments conducted with group of humans looking for a target with limited sensing capabilities solving. Then we describe the heuristics extracted from the observation and analysis of their behavior. Finally we implemented these heuristics within khepera-like autonomous mobile robots facing the same tasks. We show that the control architecture can be experimentally validated to some extent thanks to this approach.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:3177
Deposited By:Nicolas Bredeche
Deposited On:05 January 2008