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Evolved Transistor Array Robot Controllers.

Michael Garvie1, Ittai Flascher2, Andrew Philippides3

  • 1Department of Informatics, University of Sussex, Brighton, BN1 9QJ, UK m.garvie@sussex.ac.uk.

Evolutionary Computation
|May 2, 2020
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Summary
This summary is machine-generated.

Researchers evolved robot control circuits directly in analog hardware using a field-programmable transistor array (FPTA). This enabled robots to perform complex tasks, including voice-controlled navigation and target acquisition, even with noisy sensor data.

Keywords:
Evolvable hardwaredimensionality reduction.evolutionary roboticsevolved analog circuitsevolved visual featuresfeature selectionfield programmable transistor arrayincremental evolutionvisually guided behaviourword recognition

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Area of Science:

  • Robotics
  • Analog Electronics
  • Evolutionary Computation

Background:

  • Traditional robot control relies on complex software and digital systems.
  • Integrating control and sensing in physical hardware presents significant challenges.
  • Evolving analog circuits offers a novel approach to real-time robot control.

Purpose of the Study:

  • To demonstrate the first use of a field-programmable transistor array (FPTA) for evolving robot control circuits directly in analog hardware.
  • To develop controllers for visually guided behaviors and voice command recognition in a physical robot.
  • To investigate the capability of evolved analog circuits to handle noisy, real-time sensor data.

Main Methods:

  • Utilized a field-programmable transistor array (FPTA) to evolve analog control circuits.
  • Implemented incremental evolution of controllers for visually guided behaviors like target finding.
  • Co-evolved visual features with controllers for integrated dimensionality reduction and feature extraction.
  • Developed a novel simulation method for evaluating controllers connected to the FPTA before real-world transfer.
  • Addressed circuit replication by evolving controllers functional across multiple FPTA areas.
  • Developed a methodology for analyzing evolved analog circuits.

Main Results:

  • Successfully evolved controllers for a physical robot performing complex, visually guided tasks.
  • Achieved voice control of the robot by evolving circuits for spoken command recognition.
  • Demonstrated the robustness of evolved analog circuits in handling noisy visual sensor data in real-time.
  • Showcased seamless transfer of evolved controllers from simulation to the physical robot.
  • Validated the superior evolvability of the transistor array medium through comparative experiments.

Conclusions:

  • Field-programmable transistor arrays provide a powerful platform for evolving complex analog robot control systems.
  • Evolved analog circuits can effectively manage noisy sensor data and enable sophisticated behaviors.
  • The integrated approach of co-evolving features and controllers enhances robot adaptability and performance.
  • This methodology offers a promising pathway for creating more autonomous and responsive robots.