COACHES: An assistance multi-robot system in public areas

Abstract

In this paper, we present a robust system of self- directed autonomous robots evolving in a complex and public spaces and interacting with people. This system integrates highlevel skills of environment modeling using knowledge-based modeling and reasoning and scene understanding with robust image and video analysis, distributed autonomous decision- making using Markov decision process and Petri-Net planning, short-term interacting with humans and robust and safe navigation in overcrowding spaces. This system has been deployed in a variety of public environments such as a shopping mall, a center of congress and in a lab to assist people and visitors. The results are very satisfying showing the effectiveness of the system and going beyond just a simple proof of concepts.