Design of a Hybrid Powered 2D Biped Walking Machine for Studying Rough Terrain Locomotion

Author(s):  
B.C. Baker ◽  
T.N. Faddis ◽  
G.P. Strunk
Author(s):  
Hongfei Wang ◽  
Shimeng Li ◽  
Yuan F. Zheng ◽  
Taegoo Kim ◽  
Paul Oh
Keyword(s):  

Author(s):  
Masaki Ogino ◽  
Hiroyuki Toyama ◽  
Sawa Fuke ◽  
Norbert Michael Mayer ◽  
Ayako Watanabe ◽  
...  

1993 ◽  
Vol 10 (4) ◽  
pp. 531-555 ◽  
Author(s):  
Ching-Long Shih ◽  
William A. Gruver ◽  
Tsu-Tian Lee

2001 ◽  
Vol 44 (3) ◽  
pp. 724-730 ◽  
Author(s):  
Hiroaki FUNABASHI ◽  
Yukio TAKEDA ◽  
Shigenari ITOH ◽  
Masaru HIGUCHI

2012 ◽  
Vol 24 (1) ◽  
pp. 37-46 ◽  
Author(s):  
Tadayoshi Aoyama ◽  
◽  
Kosuke Sekiyama ◽  
Yasuhisa Hasegawa ◽  
Toshio Fukuda ◽  
...  

This paper deals with the 3-D biped walking of a humanoid type robot over rough terrain. We previously proposed efficient 3-D biped walking control using Passive Dynamic Autonomous Control (PDAC) based on the assumption of point-contact and virtual holonomic constraint of robot joints. Walking adaptability has not, however, been analyzed. We thus analyze the environmental adaptability of PDAC-based walking method in this paper. The robot is modeled as a variable-length 3-D inverted pendulum whose dynamics is modeled as a 2-D autonomous system by applying PDAC. We analyze the stability of the 2-D autonomous system using a Poincaré map and derive the stable range of uneven height over rough terrain. We then experimentally validate 3-D biped walking on unknown rough terrain using our humanoid type robot, Gorilla Robot III.


1989 ◽  
Vol 1 (2) ◽  
pp. 253-262 ◽  
Author(s):  
Rodney A. Brooks

Most animals have significant behavioral expertise built in without having to explicitly learn it all from scratch. This expertise is a product of evolution of the organism; it can be viewed as a very long-term form of learning which provides a structured system within which individuals might learn more specialized skills or abilities. This paper suggests one possible mechanism for analagous robot evolution by describing a carefully designed series of networks, each one being a strict augmentation of the previous one, which control a six-legged walking machine capable of walking over rough terrain and following a person passively sensed in the infrared spectrum. As the completely decentralized networks are augmented, the robot's performance and behavior repertoire demonstrably improve. The rationale for such demonstrations is that they may provide a hint as to the requirements for automatically building massive networks to carry out complex sensory-motor tasks. The experiments with an actual robot ensure that an essence of reality is maintained and that no critical disabling problems have been ignored.


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