Authors:
Manfred Hild
;
Christian Thiele
and
Christian Benckendorff
Affiliation:
Humboldt-Universität zu Berlin, Germany
Keyword(s):
Neural network architectures, Distributed systems, Modular implementations, Humanoid robotics.
Related
Ontology
Subjects/Areas/Topics:
Adaptive Architectures and Mechanisms
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bio-Inspired and Humanoid Robotics
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Collective & Distributed Intelligent Systems and Dynamics
;
Computational Intelligence
;
Enterprise Information Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Modular Implementation of Artificial Neural Networks
;
Neural Network Software and Applications
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
Humanoid robots are complex systems that require considerable processing power. This applies both for low-level sensorimotor loops, as well as for image processing and higher level deliberative algorithms. We present the distributed architecture DISTAL which is able to provide the processing power of large neural networks without relying on a central processor. The architecture successfully copes with runtime-metamorphoses of modular robots, such as the humanoid robot MYON, the body parts of which can be detached and reattached during runtime. We detail the implementation of DISTAL on 32-bit ARM RISC processors, describe the underlying neural byte-code (NBC) of neurons and synapses, and also depict the graphical application software BRAINDESIGNER which releases the user from program coding.