Neural control of a modular multi-legged walking machine: Simulation and hardware

  • Authors:

  • Arndt von Twickel;Manfred Hild;Torsten Siedel;Vishal Patel;Frank Pasemann

  • Affiliations:

  • Institute of Cognitive Science, Department Neurocybernetics, University of Osnabrück, 49069 Osnabrück, Germany;Institut für Informatik, LFG Künstliche Intelligenz, Humboldt-Universität zu Berlin, 10099 Berlin, Germany;Institut für Informatik, LFG Künstliche Intelligenz, Humboldt-Universität zu Berlin, 10099 Berlin, Germany;Institute of Cognitive Science, Department Neurocybernetics, University of Osnabrück, 49069 Osnabrück, Germany;Institute of Cognitive Science, Department Neurocybernetics, University of Osnabrück, 49069 Osnabrück, Germany

  • Venue:
  • Robotics and Autonomous Systems
  • Year:
  • 2012

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Abstract

The modular walking machine Octavio is a bio-inspired robot designed to serve as a testbed for modular neural locomotion control. It consists of up to eight control- and energy-autonomous leg modules, each equipped with 3 active and 2 passive compliant joints and various proprioceptive sensors. Legs may be either used in single leg (treadmill) experiments or can be quickly attached to and detached from bodies with different morphologies. Body morphologies include 4-, 6- and 8-legged machines. Neurocybernetic control is developed and optimized using evolutionary techniques together with a physical simulation of the machine and its environment. This article gives an overview of the machines mechanics, electronics, firmware, configuration and control software. Simple examples demonstrate how the behavior of the simulated and the physical machines are controlled by e.g. neurobiologically motivated modular neural networks.