Authors:
Juan M. Nogales
and
Gina Maira Barbosa de Oliveira
Affiliation:
Federal University of Uberlandia, Brazil
Keyword(s):
Task Allocation, Foraging, Adaptability, Cooperation, Autonomy.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Autonomous Systems
;
Bioinformatics
;
Biomedical Engineering
;
Cognitive Robotics
;
Cooperation and Coordination
;
Distributed and Mobile Software Systems
;
Distributed Problem Solving
;
Enterprise Information Systems
;
Group Decision Making
;
Informatics in Control, Automation and Robotics
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Mobile Agents
;
Multi-Agent Systems
;
Operational Research
;
Robot and Multi-Robot Systems
;
Robotics and Automation
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
In this paper, robots have to distribute themselves across a set of regions where they will serve in foraging
tasks, transporting objects repetitively. Each region stores information about the performance of the subgroup
of robots serving that region. Robots can also share information between them and identify which region is
offering better conditions to forage. In particular, each region has a different rate to recover recently removed
objects, which demands a different number of robot foragers. We explore the effects of the network structure
in robot distribution and their performance. Results indicate a small dependence of robot-robot connections
and a great dependence of robot-environment interaction. Since cooperative robots are going after a global
goal, the proposed distribution rules combined with environmental aids allowed them to make better decisions
autonomously, increasing the number of transported objects and reducing the number of travels.