ICRA 2011 Paper Abstract


Paper TuA102.1

Martini, Simone (UniversitÓ di Pisa), Fagiolini, Adriano (University of Pisa), Zichittella, Giancarlo (University of Pisa), Egerstedt, Magnus (Georgia Institute of Technology), Bicchi, Antonio (University of Pisa)

Decentralized Classification in Societies of Autonomous and Heterogenous Robots

Scheduled for presentation during the Regular Sessions "Agent-Based Systems I" (TuA102), Tuesday, May 10, 2011, 08:20−08:35, Room 3C

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on March 30, 2020

Keywords Agent-Based Systems, Autonomous Agents, Distributed Robot Systems


This paper addresses the classification problem for a set of autonomous robots that interact with each other. The objective is to classify agents that "behave'' in "different way'', due to their own physical dynamics or to the interaction protocol they are obeying to, as belonging to different "species''. This paper describes a technique that allows a decentralized classification system to be built in a systematic way, once the hybrid models describing the behavior of the different species are given. This technique is based on a decentralized identification mechanism, by which every agent classifies its neighbors using only local information. By endowing every agent with such a local classifier, the overall system is enhanced with the ability to run behaviors involving individuals of the same species as well as of different ones. The mechanism can also be used to measure the level of cooperativeness of neighbors and to discover possible intruders among them. General applicability of the proposed solution is shown through examples of multi-agent systems from Biology and from Robotics.



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