Evolutionary neurocontrollers for autonomous mobile robots
Neural Networks - Special issue on neural control and robotics: biology and technology
A Multi-robot Surveillance System Simulated in Gazebo
IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
Is situated evolution an alternative for classical evolution?
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Coordinated multi-robot exploration
IEEE Transactions on Robotics
Open-ended evolution as a means to self-organize heterogeneous multi-robot systems in real time
Robotics and Autonomous Systems
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One of the main challenges in the operation of multirobot systems is to find ways for them to adapt to changing situations and even objectives without any type of central control. In this work we propose a real time coevolutionary strategy based on Embodied Evolution (EE) approaches that provides a means to achieve this end. The main inspiration for this approach comes from the field of artificial life combined with some of the notions on the distribution of utility functions as proposed by the multiagent systems literature. The solution has been tested on different real life problems involving robot teams. In particular, in this paper the work is aimed at the coordination of sets of robots for performing monitoring and surveillance operations such as the ones required on ship tanks and hulls. Nevertheless, the approach is general enough to be applied to many other tasks in several fields.