Artificial neural nets for controlling a 6-legged walking system
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Walking: a complex behavior controlled by simple networks
Adaptive Behavior - Special issue on computational neuroethology
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
Self organisation in a simple task of motor control
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
The evolution of cognition: from first order to second order embodiment
ZiF'06 Proceedings of the Embodied communication in humans and machines, 2nd ZiF research group international conference on Modeling communication with robots and virtual humans
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The motor behavior of stick insects climbing over large gaps has already been the subject of many experimental studies. The searching movement of the legs after stepping into the gap is analyzed in the first part of this study. Based on these and earlier biological results, a simulation study is carried out using WALKNET, a neural network model of the stick insect walking system. Five new modules are implemented into the model in the form of a unit assembly system. The performance of the enhanced model is evaluated in a series of tests designed based on previous biological experiments. The simu lation study shows that with only four new modules (for searching movements, velocity control, a load effect and short steps), the performance of the model in a simulated gap crossing situation can be improved beyond the performance of the biological system under comparable conditions.