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Adaptive Autonomy in a Search and Rescue Scenario

Fulltext:


Publication Type:

Conference/Workshop Paper

Venue:

12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems

DOI:

10.1109/SASO.2018.00026


Abstract

Adaptive autonomy plays a major role in the design of multi-robots and multi-agent systems, where the need of collaboration for achieving a common goal is of primary importance. In particular, adaptation becomes necessary to deal with dynamic environments, and scarce available resources. In this paper, a mathematical framework for modelling the agents’ willingness to interact and collaborate, and a dynamic adaptation strategy for controlling the agents’ behavior, which accounts for factors such as progress toward a goal and available resources for completing a task among others, are proposed. The performance of the proposed strategy is evaluated through a fire rescue scenario, where a team of simulated mobile robots need to extinguish all the detected fires and save the individuals at risk, while having limited resources. The simulations are implemented as a ROS-based multi agent system, and results show that the proposed adaptation strategy provides a more stable performance than a static collaboration policy.

Bibtex

@inproceedings{Frasheri 5178,
author = {Mirgita Frasheri and Baran {\c{C}}{\"u}r{\"u}kl{\"u} and Mikael Ekstr{\"o}m and Alessandro Papadopoulos},
title = {Adaptive Autonomy in a Search and Rescue Scenario},
pages = {150--155},
month = {September},
year = {2018},
booktitle = {12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems},
url = {http://www.es.mdh.se/publications/5178-}
}