The society of mind
Evolutionary neurocontrollers for autonomous mobile robots
Neural Networks - Special issue on neural control and robotics: biology and technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolution of Controllers from a High-Level Simulator to a High DOF Robot
ICES '00 Proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware
Biologically Inspired Neural Controllers for Motor Control in a Quadruped Robot
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
COOPERATIVE COEVOLUTION OF MULTI-AGENT SYSTEMS
COOPERATIVE COEVOLUTION OF MULTI-AGENT SYSTEMS
Incremental Evolution of Complex General Behavior
Incremental Evolution of Complex General Behavior
Solving non-Markovian control tasks with neuroevolution
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Tactical modularity for evolutionary animats
Proceedings of the 2006 conference on Artificial Intelligence Research and Development
Embodying cognitive abilities: categorization
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Evolving the walking behaviour of a 12 DOF quadruped using a distributed neural architecture
BioADIT'06 Proceedings of the Second international conference on Biologically Inspired Approaches to Advanced Information Technology
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The implementation in a robot of the coordination between different sensors and actuators in order to achieve a task requires a high formulation and modelisation effort, specially when the number of sensors/actuators and degrees of freedom available in the robot is huge. This paper introduces a highly distributed architecture that is independent from the robot platform, capable of the generation of such a coordination in an automatic way by using evolutionary methods. The architecture is completely neural network based and it allows the control of the whole robot for, in principle, any type of task based on sensory-motor coordination. The article shows how the proposed architecture is capable of controlling an Aibo robot for the performance of three different difficult tasks (standing, standing up and walking) using exactly the same neural distribution. It is also expected that it will be directly scalable for higher levels of control and general design in evolutionary robotics.