Physical Validation of a Synchronization and Formation Control Algorithm for Multi-Agent Robotic Systems

This work focuses on the physical validation of a synchronization and formation control method for multi-agent systems. The method is based on a modified consensus equation, minimally rigid graphs, and flat tension functions. The goal is to bring a group of agents to a certain formation, and then lead them to a common goal, while avoiding obstacles. We used Pololu 3Pi+ differential robots with added wireless communication capabilities, and we ran our experiments on a 3.8 × 4.8 m platform with 6 OptiTrack motion capture cameras. We achieved over 95% overall success in various scenarios, both in simulations and in physical trials. The robotic agents were able to keep the formation as closely as possible, and they adjusted their positions and velocities for a more flexible formation, when obstacles were present, reaching the desired goal as a synchronized swarm.

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Publication Details

Published
2024-11-27
DOI
https://doi.org/10.1109/concapan63470.2024.10933866
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Physical Validation of a Synchronization and Formation Control Algorithm for Multi-Agent Robotic Systems

J. L. Rodriguez, Luis Alberto Rivera
Distributed Control Multi-Agent Systems
article

Physical Validation of a Synchronization and Formation Control Algorithm for Multi-Agent Robotic Systems

J. L. Rodriguez, Luis Alberto Rivera
article en

Abstract

This work focuses on the physical validation of a synchronization and formation control method for multi-agent systems. The method is based on a modified consensus equation, minimally rigid graphs, and flat tension functions. The goal is to bring a group of agents to a certain formation, and then lead them to a common goal, while avoiding obstacles. We used Pololu 3Pi+ differential robots with added wireless communication capabilities, and we ran our experiments on a 3.8 × 4.8 m platform with 6 OptiTrack motion capture cameras. We achieved over 95% overall success in various scenarios, both in simulations and in physical trials. The robotic agents were able to keep the formation as closely as possible, and they adjusted their positions and velocities for a more flexible formation, when obstacles were present, reaching the desired goal as a synchronized swarm.

Universidad del Valle de Guatemala (GT)
Openalex Percentile: Top 66%
Distributed Control Multi-Agent Systems
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