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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

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Self-organized coordinated motion in groups of physically connected robots.

Gianluca Baldassarre¹, Vito Trianni, Michael Bonani

¹Laboratory of Autonomous Robotics and Artificial Life, Istituto di Scienze e Tecnologie della Cognizione, Consiglio Nazionale delle Ricerche, 00185 Rome, Italy. gianluca.baldassarre@istc.cnr.it

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|February 7, 2007

Summary

Researchers developed a neural controller for collective robotics, enabling robots to coordinate tasks using only local sensory information. This controller, evolved in simulation, successfully transferred to real robots and generalized to new conditions.

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Area of Science:

Collective Robotics
Artificial Intelligence
Control Systems

Background:

Designing decentralized control systems for multi-robot systems is a key challenge.
Robots often need to coordinate actions without a central command structure.

Purpose of the Study:

To investigate a simple neural controller for achieving coherent behavior in physically assembled robots.
To enable coordinated motion using only local sensory input.

Main Methods:

Artificial evolution was used to synthesize a neural controller in a simulated environment.
The controller's performance was evaluated after transferring it to real robots.
Generalization to different group configurations and connection mechanisms was tested.

Main Results:

The evolved neural controller facilitated coordinated-motion behaviors in robots.
The controller demonstrated robustness, allowing successful transfer from simulation to physical robots.
The controller generalized effectively to varied group sizes, shapes, and connection types.

Conclusions:

A decentralized neural controller can achieve robust, coordinated behavior in collective robotics.
Local sensory information is sufficient for effective robot group coordination.
Evolved controllers offer a promising approach for real-world robotic applications.