Chapter

Evolutionary Robotics. From Intelligent Robotics to Artificial Life

Volume 2217 of the series Lecture Notes in Computer Science pp 38-61

Date:

Evolution of Spiking Neural Controllers for Autonomous Vision-Based Robots

  • Dario FloreanoAffiliated withEvolutionary & Adaptive Systems, Institute of Robotics Swiss Federal Institute of Technology
  • , Claudio MattiussiAffiliated withEvolutionary & Adaptive Systems, Institute of Robotics Swiss Federal Institute of Technology

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Abstract

We describe a set of preliminary experiments to evolve spiking neural controllers for a vision-based mobile robot. All the evolutionary experiments are carried out on physical robots without human intervention. After discussing how to implement and interface these neurons with a physical robot, we show that evolution finds relatively quickly functional spiking controllers capable of navigating in irregularly textured environments without hitting obstacles using a very simple genetic encoding and fitness function. Neuroethological analysis of the network activity let us understand the functioning of evolved controllers and tell the relative importance of single neurons independently of their observed firing rate. Finally, a number of systematic lesion experiments indicate that evolved spiking controllers are very robust to synaptic strength decay that typically occurs in hardware implementations of spiking circuits.