The Transfer of Evolved Artificial Immune System Behaviours between Small and Large Scale Robotic Platforms

TL;DR

This study shows that behaviors evolved in simulation on small robots can be transferred to larger, different robots using an adaptive immune system approach, enabling successful navigation and object-tracking tasks.

Contribution

It introduces a method for transferring evolved behaviors between different robotic platforms using an immune system-inspired control architecture.

Findings

Transferred behaviors enable navigation and object tracking on larger robots.

Adaptive AIS mechanism is crucial for successful behavior transfer.

Behaviors evolved in simulation generalize across robot sizes and types.

Abstract

This paper demonstrates that a set of behaviours evolved in simulation on a miniature robot (epuck) can be transferred to a much larger scale platform (a virtual Pioneer P3-DX) that also differs in shape, sensor type, sensor configuration and programming interface. The chosen architecture uses a reinforcement learning-assisted genetic algorithm to evolve the epuck behaviours, which are encoded as a genetic sequence. This sequence is then used by the Pioneers as part of an adaptive, idiotypic artificial immune system (AIS) control architecture. Testing in three different simulated worlds shows that the Pioneer can use these behaviours to navigate and solve object-tracking tasks successfully, as long as its adaptive AIS mechanism is in place.