Biologically Inspired Motion Design Approaches for Humanoids and Walking Machines

Author(s):  
Teresa Zielińska
Author(s):  
Rüdiger Dillmann ◽  
Jan Albiez ◽  
Bernd Gaßmann ◽  
Thilo Kerscher ◽  
Marius Zöllner

This article presents a set of methods used to support the design and control of biologically inspired walking machines. Starting with a description of the general system design idea, an example for the design of the mechanical construction, a computer supported design procedure for the control architecture and the description of a three-dimensional world model to be used as knowledge base is given. The focus of this paper is on the engineering and integration process and the interrelation between the different phases of the design process.


2007 ◽  
Vol 26 (3) ◽  
pp. 301-331 ◽  
Author(s):  
Poramate Manoonpong ◽  
Frank Pasemann ◽  
Hubert Roth

2014 ◽  
pp. 75-86
Author(s):  
Poramate Manoonpong ◽  
Frank Pasemann ◽  
Hubert Roth

In this article, a modular neurocontroller is presented. It has the capability to generate a reactive behavior of walking machines. The neurocontroller is formed on the basis of a modular structure. It consists of the three different functionality modules: neural preprocessing, a neural oscillator network and velocity regulating networks. Neural preprocessing is for sensory signal processing. The neural oscillator network, based on a central pattern generator, generates the rhythmic movement for basic locomotion of the walking machines while the velocity regulating networks change the walking directions of the machines with respect to the sensory inputs. As a result, this neurocontroller enables the machines to explore in- and out-door environments by avoiding obstacles and escaping from corners or deadlock situations. It was firstly developed and tested on a physical simulation environment, and then was successfully transferred to the six-legged walking machine AMOS-WD06.


2012 ◽  
Author(s):  
Kenneth Breuer ◽  
Sharon Swartz ◽  
Jaime Peraire ◽  
Mark Drela ◽  
David Willis ◽  
...  

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