TY - JOUR
T1 - Walknet - A biologically inspired network to control six-legged walking
AU - Cruse, Holk
AU - Kindermann, Thomas
AU - Schumm, Michael
AU - Dean, Jeffrey
AU - Schmitz, Josef
PY - 1998/1/1
Y1 - 1998/1/1
N2 - To investigate walking we perform experimental studies on animals in parallel with software and hardware simulations of the control structures and the body to be controlled. Therefore, the primary goal of our simulation studies is not so much to develop a technical device, but to develop a system which can be used as a scientific tool to study insect walking. To this end, the animal should copy essential properties of the animals. In this review, we will first describe the basic behavioral properties of hexapod walking, as the are known from stick insects. Then we describe a simple neural network called Walknet which exemplifies these properties and also shows some interesting emergent properties. The latter arise mainly from the use of the physical properties to simplify explicit calculations. The model is simple too, because it uses only static neuronal units. Finally, we present some new behavioral results. To investigate walking we perform experimental studies on animals in parallel with software and hardware simulations of the control structures and the body to be controlled. Therefore, the primary goal of our simulation studies is not so much to develop a technical device, but to develop a system which can be used as a scientific tool to study insect walking. To this end, the animat should copy essential properties of the animals. In this review, we will first describe the basic behavioral properties of hexapod walking, as the are known from stick insects. Then we describe a simple neural network called Walknet which exemplifies these properties and also shows some interesting emergent properties. The latter arise mainly from the use of the physical properties to simplify explicit calculations. The model is simple too, because it uses only static neuronal units. Finally, we present some new behavioral results.
AB - To investigate walking we perform experimental studies on animals in parallel with software and hardware simulations of the control structures and the body to be controlled. Therefore, the primary goal of our simulation studies is not so much to develop a technical device, but to develop a system which can be used as a scientific tool to study insect walking. To this end, the animal should copy essential properties of the animals. In this review, we will first describe the basic behavioral properties of hexapod walking, as the are known from stick insects. Then we describe a simple neural network called Walknet which exemplifies these properties and also shows some interesting emergent properties. The latter arise mainly from the use of the physical properties to simplify explicit calculations. The model is simple too, because it uses only static neuronal units. Finally, we present some new behavioral results. To investigate walking we perform experimental studies on animals in parallel with software and hardware simulations of the control structures and the body to be controlled. Therefore, the primary goal of our simulation studies is not so much to develop a technical device, but to develop a system which can be used as a scientific tool to study insect walking. To this end, the animat should copy essential properties of the animals. In this review, we will first describe the basic behavioral properties of hexapod walking, as the are known from stick insects. Then we describe a simple neural network called Walknet which exemplifies these properties and also shows some interesting emergent properties. The latter arise mainly from the use of the physical properties to simplify explicit calculations. The model is simple too, because it uses only static neuronal units. Finally, we present some new behavioral results.
KW - Decentralized control
KW - Leg coordination
KW - Positive feedback
KW - Situatedness
KW - Six-legged robot
KW - Stick insect
KW - Walking
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U2 - 10.1016/S0893-6080(98)00067-7
DO - 10.1016/S0893-6080(98)00067-7
M3 - Article
SN - 0893-6080
VL - 11
SP - 1435
EP - 1447
JO - Neural Networks
JF - Neural Networks
IS - 7-8
ER -