A Neural Network Based Control System for a Mobile Robot Employing Link Mechanism

Sato, Mitsuhisa; Ishii, Kazuki

doi:10.1109/aim.2005.1501028

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…In the previous paper [6], a mobile robot bZaurusQ ( Fig. 1(a)) has been developed using the similar kind of linkage structure, and its maneuverability has been verified through simulations and experiments.…”

Section: Wheel Type Mobile Robot Bzaurusqmentioning

confidence: 99%

A neural network based controller for a wheel type mobile robot

Sato

Ishii

2006

International Congress Series

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Section: Wheel Type Mobile Robot Bzaurusqmentioning

confidence: 99%

A neural network based controller for a wheel type mobile robot

Sato

Ishii

2006

International Congress Series

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“…In the previous papers, a mobile robot "Zaurus" (Fig. 1A) was developed using the linkage structure, and its maneuverability has been verified through simulation and experiments [4,5]. The result of climbing over the bump of 0.20 m, which corresponds to twice the diameter of the wheel, has been achieved.…”

Section: Introductionmentioning

confidence: 98%

Performance evaluation of a neural network controller system for a wheel type mobile robot

Sato

Kanda

Ishii

2007

International Congress Series

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“…e.g., [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] Unfortunately, many important applications involve confounding aspects that prove challenging for those approaches. In particular, this may include unpredictable and unforeseeably evolving environment conditions or other factors pertinent to robot's task, as well as under-defined or unstructured conditions or situations.…”

Section: Introductionmentioning

confidence: 99%

Neurobiomimetic constructs for intelligent unmanned systems and robotics

2014

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This paper discusses a paradigm we refer to as neurobiomimetic, which involves emulations of brain neuroanatomy and neurobiology aspects and processes. Neurobiomimetic constructs include rudimentary and down-scaled computational representations of brain regions, sub-regions, and synaptic connectivity. Many different instances of neurobiomimetic constructs are possible, depending on various aspects such as the initial conditions of synaptic connectivity, number of neuron elements in regions, connectivity specifics, and more, and we refer to these instances as 'animats'. While downscaled for computational feasibility, the animats are very large constructs; the animats implemented in this work contain over 47,000 neuron elements and over 720,000 synaptic connections. The paper outlines aspects of the animats implemented, spatial memory and learning cognitive task, the virtual-reality environment constructed to study the animat performing that task, and discussion of results. In a broad sense, we argue that the neurobiomimetic paradigm pursued in this work constitutes a particularly promising path to artificial cognition and intelligent unmanned systems. Biological brains readily cope with challenges of real-life tasks that consistently prove beyond even the most sophisticated algorithmic approaches known. At the cross-over point of neuroscience, cognitive science and computer science, paradigms such as the one pursued in this work aim to mimic the mechanisms of biological brains and as such, we argue, may lead to machines with abilities closer to those of biological species.

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A Neural Network Based Control System for a Mobile Robot Employing Link Mechanism

Cited by 7 publications

References 8 publications

A neural network based controller for a wheel type mobile robot

A neural network based controller for a wheel type mobile robot

Performance evaluation of a neural network controller system for a wheel type mobile robot

Neurobiomimetic constructs for intelligent unmanned systems and robotics

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