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Related Experiment Video

Updated: Mar 8, 2026

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

Multi-Robot Coalitions Formation with Deadlines: Complexity Analysis and Solutions.

Jose Guerrero¹, Gabriel Oliver¹, Oscar Valero¹

¹University of the Balearic Islands, Mathematical and Computer Science Department, Palma de Mallorca, Illes Balears, Spain.

|January 25, 2017

Summary

This study introduces a formal model for multi-robot task allocation, addressing physical interference. New algorithms achieve over 80% of optimal solutions with reduced execution time.

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Area of Science:

Robotics
Artificial Intelligence
Operations Research

Background:

Multi-robot task allocation is crucial for system efficiency, especially under deadlines.
Physical interference between robots accessing shared points degrades performance.
Existing allocation algorithms do not formally model interference effects.

Purpose of the Study:

To formally describe multi-robot task allocation incorporating physical interference.
To analyze the complexity of interference-aware task allocation.
To determine conditions for solving the allocation problem using integer linear programming.

Main Methods:

Development of a formal model for multi-robot task allocation with interference.
Analysis of the computational complexity of the proposed model.
Formulation of conditions for optimal solution via integer linear programming.
Comparison of new algorithms against prior methods and optimal solutions.

Main Results:

The first formal description of multi-robot task allocation with a physical interference model.
Identification of conditions enabling optimal solutions through integer linear programming.
New task allocation algorithms achieve >80% of the median optimal solution.
Significant reduction in execution time compared to previous algorithms.

Conclusions:

The developed interference model provides a foundation for more realistic multi-robot task allocation.
Integer linear programming offers an efficient path to optimal solutions under specific conditions.
The proposed algorithms balance solution quality and computational efficiency effectively.