Towards a distributed solution to multi-robot task allocation problem with energetic and spatiotemporal constraints

Farouq Zitouni, Saad Harous, Ramdane Maamri

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This paper tackles the Multi-Robot Task Allocation problem. It consists of two distinct sets: a set of tasks (requiring resources), and a set of robots (offering resources). Then, the tasks are allocated to robots while optimizing a certain objective function subject to some constraints; e.g., allocating the maximum number of tasks, minimizing the distances traveled by the robots, etc. Previous works mainly optimized the temporal and spatial constraints, but no work focused on energetic constraints. Our main contribution is the introduction of energetic constraints on multi-robot task allocation problems. In addition, we propose an allocation method based on parallel distributed guided genetic algorithms and compare it to two state-of-the-art algorithms. The performed simulations and obtained results show the effectiveness and scalability of our solution, even in the case of a large number of robots and tasks. We believe that our contribution is applicable in many contemporary areas of research such as smart cities and related topics.

Original languageEnglish
Pages (from-to)3-24
Number of pages22
JournalComputer Science
Volume21
Issue number1
DOIs
Publication statusPublished - 2020

Keywords

  • Energetic constraints
  • Multi-robot systems
  • Multi-robot task allocation
  • Objective function
  • Parallel distributed guided genetic algorithms
  • Spatial constraints
  • Temporal constraints

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Modelling and Simulation
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics
  • Artificial Intelligence

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