Title :
Deriving minimal sensory configurations for evolved cooperative robot teams
Author :
Watson, James ; Nitschke, Geoff
Author_Institution :
Department of Computer Science, University of Cape Town, Cape Town, South Africa
Abstract :
This paper presents a study on the impact of different robot sensory configurations (morphologies) in simulated robot teams that must accomplish a collective (cooperative) behavior task. The study´s objective was to investigate if effective collective behaviors could be efficiently evolved given minimal morphological complexity of individual robots in an homogenous team. A range of sensory configurations are tested in company with evolved controllers for a collective construction task. Results indicate that a minimal sensory configuration yields the highest task performance, and increasing the complexity of the sensory configuration does not yield an increased task performance.
Keywords :
Artificial neural networks; Collision avoidance; Morphology; Robot kinematics; Robot sensing systems;
Conference_Titel :
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location :
Sendai, Japan
DOI :
10.1109/CEC.2015.7257271