Networks of spiking neurons: the third generation of neural network models
Transactions of the Society for Computer Simulation International - Special issue: simulation methodology in transportation systems
Chemotaxis control by linear recurrent networks
CNS '97 Proceedings of the sixth annual conference on Computational neuroscience : trends in research, 1998: trends in research, 1998
Biologically Inspired Robots: Serpentile Locomotors and Manipulators
Biologically Inspired Robots: Serpentile Locomotors and Manipulators
Journal of Global Optimization
A novel neural network analysis method applied to biological neural networks
A novel neural network analysis method applied to biological neural networks
A model of motor control of the nematode C. elegans with neuronal circuits
Artificial Intelligence in Medicine
Mechanics of precurved-tube continuum robots
IEEE Transactions on Robotics
A Biologically Accurate 3D Model of the Locomotion of Caenorhabditis Elegans
BIOSCIENCESWORLD '10 Proceedings of the 2010 International Conference on Biosciences
A C. elegans-inspired micro-robot with polymeric actuators and online vision
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Neurocomputing
Differential Evolution: A Survey of the State-of-the-Art
IEEE Transactions on Evolutionary Computation
A General Internal Model Approach for Motion Learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In this work, a 3D undulatory locomotion model inspired by Caenorhabditis elegans is constructed. Following the anatomical structure of C. elegans, the body of the model is represented as a multi-joint rigid link system with 12 links. The angle between two consecutive links is determined by the muscle lengths in four quadrants that are controlled by the nervous system. The nervous system of this locomotion model is represented by a dynamic neural network (DNN) that involves three parts: head DNN, central pattern generator (CPG), and body DNN. The head DNN decides turning or not, and CPG produces the sinusoid waves that are transmitted through the body DNN to control the lengths of muscles. The 3D locomotion behavior is achieved by using the DNN to control the muscle lengths, and then using the muscle lengths to control the angles between two consecutive links on both horizontal plane and vertical plane. In this work, the relations between the outputs of DNN and muscle lengths, as well as the muscle lengths and the angles between two consecutive links, are determined. Furthermore, due to the learning capability of DNN, a set of nonlinear functions that are designed to represent the chemotaxis behaviors of C. elegans are learned by the head DNN using Differential Evolution Algorithm. The testing results show good 3D performance of this locomotion model in both forward and backward locomotion, as well as slight turn and @W turn. Furthermore, this locomotion model performs the chemotaxis behaviors of finding food and avoiding toxin successfully. Finally, quantitative analyses by comparing with the experiment results are provided to verify the realness and effectiveness of this locomotion model, which could serve as a prototype for the worm-like robot.