Physical Validation of PSO and ACO Based Algorithms for Multi-Agent Robotic Systems

This work focuses on the physical validation of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) based algorithms for trajectory planning and goal searching tasks with multi-agent robotic systems. We used Pololu 3Pi+ differential robots with added wireless communication capabiliti...

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Published inIEEE Central America and Panama Convention (CONCAPAN) pp. 1 - 6
Main Authors Menendez, Jonathan, Rivera, Luis Alberto
Format Conference Proceeding
LanguageEnglish
Published IEEE 27.11.2024
Subjects
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ISSN2687-7244
DOI10.1109/CONCAPAN63470.2024.10933832

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Abstract This work focuses on the physical validation of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) based algorithms for trajectory planning and goal searching tasks with multi-agent robotic systems. 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. Our methods consider the kinematics of differential robots and use PID based controllers to ensure smooth trajectories and safe motor speeds for the robots. In our PSO experiments, the swarms were able to reach goal positions under different conditions. In our ACO experiments, we used virtual agents to find a suitable trajectory to the goal in the test space, and a physical robot was able to follow the calculated trajectory.
AbstractList This work focuses on the physical validation of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) based algorithms for trajectory planning and goal searching tasks with multi-agent robotic systems. 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. Our methods consider the kinematics of differential robots and use PID based controllers to ensure smooth trajectories and safe motor speeds for the robots. In our PSO experiments, the swarms were able to reach goal positions under different conditions. In our ACO experiments, we used virtual agents to find a suitable trajectory to the goal in the test space, and a physical robot was able to follow the calculated trajectory.
Author Rivera, Luis Alberto
Menendez, Jonathan
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  givenname: Luis Alberto
  surname: Rivera
  fullname: Rivera, Luis Alberto
  email: larivera@uvg.edu.gt
  organization: Universidad del Valle de Guatemala,Department of Electronics, Mechatronics and Biomedical Engineering,Guatemala
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Snippet This work focuses on the physical validation of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) based algorithms for trajectory planning...
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SubjectTerms ACO
Cameras
differential robots
Motion capture
Motors
Particle swarm optimization
PSO
Robot vision systems
Robots
Swarm robotics
Trajectory
trajectory planner
Trajectory planning
Wireless communication
Title Physical Validation of PSO and ACO Based Algorithms for Multi-Agent Robotic Systems
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