Bio-inspired Decentralized Self-coordination Algorithms for Multi-heterogeneous Specialized Tasks Distribution in Multi-Robot Systems - Foundations on Natural and Artificial Computation - page 30

Bio-inspired Decentralized Self-coordination
Algorithms for Multi-heterogeneous Specialized
Tasks Distribution in Multi-Robot Systems

Yadira Quinonez, Javier de Lope, and Dar ıo Maravall

Computational Cognitive Robotics
Dept. Artificial Intelligence
Universidad Politecnica de Madrid
[e-mail], [e-mail], [e-mail]

Abstract. This paper focuses on the general problem of coordinating
multiple robots. More specifically, it addresses the self-election of het-
erogeneous specialized tasks by autonomous robots, as opposed to the
usual multi-tasks allocation problem in multi-robot systems in which an
external controller distributes the existing tasks among the individual
robots. We are rather interested on decentralized solutions in which the
robots themselves, autonomously and in an individual manner, select a
particular task so that all the existing tasks are optimally distributed
and executed. In this regard, we establish an experimental scenario and
we propose a bio-inspired solution based on threshold models to solve the
corresponding multi-tasks distribution problem. The paper ends with a
critical discussion of the experimental results.

Keywords: Multi-robot systems, bio-inspired threshold models,
multi-tasks distribution, self-coordination of multiple robots, multi-
heterogeneous specialized tasks distribution.

1 Introduction

Autonomous Multi-robot Systems is one of the characteristic applied areas of
Artificial Intelligence that has gotten an amazing growth since its inception until
today, and it has developed very significant progress in various fields of applica-
tion [1], becoming a fundamental tool to produce, work and perform dangerous
jobs on earth and beyond. Currently, important research is being focused specifi-
cally to the coordination and communication of multi-robot systems, the interest
in this field is that, these systems offer several advantages and a higher potential
with respect to the use of a single robot in performing many tasks.
Some areas of application range from industrial to military, in all these ar-
eas, the tasks are very dangerous that require greater performance, coverage
and robustness and fault tolerance. Some examples include: cooperation in the
transport or handling of parts in the industry, the exploration of land wholly or
partially unknown (e.g. an unknown planet exploration), tasks on large tracts