There are lots of good documents to read in order to pursue the Gyoomard dream. We'll try to mention a few each time in these posts.
T. Reil and P. Husbands. Evolution of Central pattern Generators for Bipedal Walking in Real-time Physics Environments
This paper uses CTRNNs which are trained by GAs to evolve the walking motion for a biped. Our first milestone in Gyoomard project is to follow the study performed in this paper and prepare our simulation environment for further research. The CTRNN acts as a central pattern generator for the biped. MathEngine physics engine is the framework for the simulation. No sensor neurons are used in this study.
G. McHale and P. Husbands, Quadrupedal locomotion: GasNets, CTRNNs and Hybrid CTRNN/PNNs compared
Several techniques for evolving sensory motor systems of a four legged creature robot are tested in the above paper. GasNets have proven to be efficient in certain situations. ODE is used. This study uses sensor neurons to sense when the limbs touch the ground. A similar study has been done by the authors to compare many more different types of networks.
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What is ODE? Is it Ordinary Differential Equations?
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