Modular Reactive Neurocontrol for Biologically Inspired Walking Machines
International Journal of Robotics Research
Robotics and Autonomous Systems
A Neural Network-Based Approach to Robot Motion Control
RoboCup 2007: Robot Soccer World Cup XI
Hardware implementation of a CPG-based locomotion control for quadruped robots
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
Gait transition and modulation in a quadruped robot: A brainstem-like modulation approach
Robotics and Autonomous Systems
Evolving central pattern generators with varying number of neurons
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part I
Pruning neural networks for a two-link robot control system
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Highly modular architecture for the general control of autonomous robots
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
ARCS'10 Proceedings of the 23rd international conference on Architecture of Computing Systems
Temporal patterns in artificial reaction networks
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Adaptive dynamic control of quadrupedal robotic gaits with artificial reaction networks
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
Single-unit pattern generators for quadruped locomotion
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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This paper presents biologically inspired neural controllers for generating motor patterns in a quadruped robot. Sets of artificial neural networks are presented which provide 1) pattern generation and gait control, allowing continuous passage from walking to trotting to galloping, 2) control of sitting and lying down behaviors, and 3) control of scratching. The neural controllers consist of sets of oscillators composed of leaky-integrator neurons, which control pairs of exor-extensor muscles attached to each joint. The networks receive sensory feedback proportional to the contraction of simulated muscles and to joint exion. Similarly, to what is observed in cats, locomotion can be initiated by either applying tonic (i.e. non-oscillating) input to the locomotion network or by sensory feedback from extending the legs. The networks are implemented in a quadruped robot. It is shown that computation can be carried out in real time and that the networks can generate the above mentioned motor behaviors.