Communications of the ACM
A distributed neural network architecture for hexapod robot locomotion
Neural Computation
Sense organs of insect legs and the selection of sensors for agile walking robots
International Journal of Robotics Research
Biologically inspired approaches to robotics: what can we learn from insects?
Communications of the ACM
Walknet—a biologically inspired network to control six-legged walking
Neural Networks - Special issue on neural control and robotics: biology and technology
The handbook of brain theory and neural networks
Reflex-oscillations in evolved single leg neurocontrollers for walking machines
Natural Computing: an international journal
Robotics and Autonomous Systems
Robotics and Autonomous Systems
Evolved neural reflex-oscillators for walking machines
IWINAC'05 Proceedings of the First international conference on Mechanisms, Symbols, and Models Underlying Cognition: interplay between natural and artificial computation - Volume Part I
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This paper outlines aspects of locomotor control in insectsthat may serve as the basis for the design of controllers forautonomous hexapod robots. Control of insect walking can beconsidered hierarchical and modular. The brain determines onset,direction, and speed of walking. Coordination is done locally in theganglia that control leg movements. Typically, networks of neuronscapable of generating alternating contractions of antagonisticmuscles (termed central pattern generators, or CPGs) control thestepping movements of individual legs. The legs are coordinated byinteractions between the CPGs and sensory feedback from the movinglegs. This peripheral feedback provides information about leg load,position, velocity, and acceleration, as well as information aboutjoint angles and foot contact. In addition, both the central patterngenerators and the sensory information that feeds them may bemodulated or adjusted according to circumstances. Consequently,locomotion in insects is extraordinarily robust and adaptable.