Biological inspiration for mechanical design and control of autonomous walking robots: towards life-like robots

Poramate Manoonpong, Florentin Wörgötter, Frank Pasemann

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

Nature apparently has succeeded in evolving biomechanics and creating neural mechanisms that allow living systems like walking animals to perform various sophisticated behaviors, e.g., different gaits, climbing, turning, orienting, obstacle avoidance, attraction, anticipation. This shows that general principles of nature can provide biological inspiration for robotic designs or give useful hints of what is possible and design ideas that may have escaped our consideration. Instead of starting from scratch, this article presents how the biological principles can be used for mechanical design and control of walking robots, in order to approach living creatures in their level of performance. Employing this strategy allows us to successfully develop versatile, adaptive, and autonomous walking robots. Versatility in this sense means a variety of reactive behaviors including memory guidance, while adaptivity implies online learning capabilities. Autonomy is an ability to function without continuous human guidance. These three key elements are achieved under modular neural control and learning. In addition, the presented neural control technique is shown to be a powerful method of solving sensor-motor coordination problems of high complexity systems.
OriginalsprogEngelsk
TidsskriftInternational Journal of Applied Biomedical Engineering
Vol/bind3
Udgave nummer1
Sider (fra-til)1-12
Antal sider12
ISSN1906-4063
StatusUdgivet - 2010
Udgivet eksterntJa

Fingeraftryk

Robots
Biomechanics
Collision avoidance
Animals
Robotics
Data storage equipment
Sensors

Citer dette

@article{6f4fe17a48884668930e790eff7a6919,
title = "Biological inspiration for mechanical design and control of autonomous walking robots: towards life-like robots",
abstract = "Nature apparently has succeeded in evolving biomechanics and creating neural mechanisms that allow living systems like walking animals to perform various sophisticated behaviors, e.g., different gaits, climbing, turning, orienting, obstacle avoidance, attraction, anticipation. This shows that general principles of nature can provide biological inspiration for robotic designs or give useful hints of what is possible and design ideas that may have escaped our consideration. Instead of starting from scratch, this article presents how the biological principles can be used for mechanical design and control of walking robots, in order to approach living creatures in their level of performance. Employing this strategy allows us to successfully develop versatile, adaptive, and autonomous walking robots. Versatility in this sense means a variety of reactive behaviors including memory guidance, while adaptivity implies online learning capabilities. Autonomy is an ability to function without continuous human guidance. These three key elements are achieved under modular neural control and learning. In addition, the presented neural control technique is shown to be a powerful method of solving sensor-motor coordination problems of high complexity systems.",
keywords = "Neural control, Biomechanics, Reactive behavior, Memory-guided behavior, Predictive behavior",
author = "Poramate Manoonpong and Florentin W{\"o}rg{\"o}tter and Frank Pasemann",
year = "2010",
language = "English",
volume = "3",
pages = "1--12",
journal = "International Journal of Applied Biomedical Engineering",
issn = "1906-4063",
number = "1",

}

Biological inspiration for mechanical design and control of autonomous walking robots : towards life-like robots. / Manoonpong, Poramate; Wörgötter, Florentin; Pasemann, Frank.

I: International Journal of Applied Biomedical Engineering , Bind 3, Nr. 1, 2010, s. 1-12.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - Biological inspiration for mechanical design and control of autonomous walking robots

T2 - towards life-like robots

AU - Manoonpong, Poramate

AU - Wörgötter, Florentin

AU - Pasemann, Frank

PY - 2010

Y1 - 2010

N2 - Nature apparently has succeeded in evolving biomechanics and creating neural mechanisms that allow living systems like walking animals to perform various sophisticated behaviors, e.g., different gaits, climbing, turning, orienting, obstacle avoidance, attraction, anticipation. This shows that general principles of nature can provide biological inspiration for robotic designs or give useful hints of what is possible and design ideas that may have escaped our consideration. Instead of starting from scratch, this article presents how the biological principles can be used for mechanical design and control of walking robots, in order to approach living creatures in their level of performance. Employing this strategy allows us to successfully develop versatile, adaptive, and autonomous walking robots. Versatility in this sense means a variety of reactive behaviors including memory guidance, while adaptivity implies online learning capabilities. Autonomy is an ability to function without continuous human guidance. These three key elements are achieved under modular neural control and learning. In addition, the presented neural control technique is shown to be a powerful method of solving sensor-motor coordination problems of high complexity systems.

AB - Nature apparently has succeeded in evolving biomechanics and creating neural mechanisms that allow living systems like walking animals to perform various sophisticated behaviors, e.g., different gaits, climbing, turning, orienting, obstacle avoidance, attraction, anticipation. This shows that general principles of nature can provide biological inspiration for robotic designs or give useful hints of what is possible and design ideas that may have escaped our consideration. Instead of starting from scratch, this article presents how the biological principles can be used for mechanical design and control of walking robots, in order to approach living creatures in their level of performance. Employing this strategy allows us to successfully develop versatile, adaptive, and autonomous walking robots. Versatility in this sense means a variety of reactive behaviors including memory guidance, while adaptivity implies online learning capabilities. Autonomy is an ability to function without continuous human guidance. These three key elements are achieved under modular neural control and learning. In addition, the presented neural control technique is shown to be a powerful method of solving sensor-motor coordination problems of high complexity systems.

KW - Neural control

KW - Biomechanics

KW - Reactive behavior

KW - Memory-guided behavior

KW - Predictive behavior

M3 - Journal article

VL - 3

SP - 1

EP - 12

JO - International Journal of Applied Biomedical Engineering

JF - International Journal of Applied Biomedical Engineering

SN - 1906-4063

IS - 1

ER -