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

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Automating the Incremental Evolution of Controllers for Physical Robots.

Andrés Faíña^1,2, Lars Toft Jacobsen², Sebastian Risi²

¹Contact author.

Artificial Life

|May 18, 2017

Summary

This study demonstrates fully autonomous evolution of robot controllers directly on hardware, overcoming the simulation-to-reality gap. It enables robots to adapt and learn in real-world environments without human intervention.

Keywords:

Evolution of physical systems (EPS)evolution in hardware evolutionary robotics

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Area of Science:

Robotics
Artificial Intelligence
Evolutionary Computation

Background:

Evolutionary robotics faces challenges like the simulation-to-reality gap.
Embodied evolution requires processes to act on real agents, not just digital objects.

Purpose of the Study:

To investigate the realization of fully autonomous evolution of robot controllers in hardware.
To address the challenge of transferring phenotypes from simulation to reality.

Main Methods:

Utilized an industrial robot and a marker-based computer vision system.
Developed an automated reconfiguration of the test environment.
Implemented incremental evolution of a neural robot controller.

Main Results:

Achieved the first instance of incremental evolution of a neural robot controller for obstacle avoidance tasks without human intervention.
Demonstrated a high level of robustness and precision in the evolved controllers.
Successfully automated the reconfiguration of the physical test environment.

Conclusions:

Fully autonomous embodied evolution of robot controllers in hardware is feasible.
The developed system can potentially expand the scope of problems addressed by embodied evolution.
Overcoming the reality gap is crucial for advancing autonomous and adaptive robots.