A Reflexive Neural Network for Dynamic Biped Walking Control

Geng, Tao; Porr, Bernd; Florentinwörgötter, Bernd

doi:10.1162/089976606776241057

Cited by 18 publications

(1 citation statement)

References 28 publications

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“…Through careful design, they exploit the passive dynamics of their own body to move forward, requiring little control or none [6][7][8][9][10]. However, the construction of bipedal machines capable of exploiting passive dynamics in different gaits remains an unsolved engineering challenge.…”

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Exploiting the passive dynamics of a compliant leg to develop gait transitions

Salazar

Carbajal

2011

Phys. Rev. E

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In the area of bipedal locomotion, the spring loaded inverted pendulum (SLIP) model has been proposed as a unified framework to explain the dynamics of a wide variety of gaits. In this paper, we present a novel analysis of the mathematical model and its dynamical properties. We use the perspective of hybrid dynamical systems to study the dynamics and define concepts such as partial stability and viability. With this approach, on the one hand, we identified stable and unstable regions of locomotion. On the other hand, we found ways to exploit the unstable regions of locomotion to induce gait transitions at a constant energy regime. Additionally, we show that simple non-constant angle of attack control policies can render the system almost always stable.

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confidence: 99%

Exploiting the passive dynamics of a compliant leg to develop gait transitions

Salazar

Carbajal

2011

Phys. Rev. E

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An Interactively Constrained Neuro-Evolution Approach for Behavior Control of Complex Robots

Rempis

Pasemann

2012

Variants of Evolutionary Algorithms for Real-World Applications

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Bipedal robotic walking control derived from analysis of human locomotion

et al. 2018

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This paper proposes the design of a bipedal robotic controller where the function between the sensory input and motor output is treated as a black box derived from human data. In order to achieve this, we investigated the causal relationship between ground contact information from the feet and leg muscle activity n human walking and calculated filter functions which transform sensory signals to motor actions. A minimal, nonlinear, and robust control system was created and subsequently analysed by applying it to our bipedal robot RunBot III without any central pattern generators or precise trajectory control. The results demonstrate that our controller can generate stable robotic walking. This indicates that complex locomotion patterns can result from a simple model based on reflexes and supports the premise that human-derived control strategies have potential applications in robotics or assistive devices.Electronic supplementary materialThe online version of this article (10.1007/s00422-018-0750-5) contains supplementary material, which is available to authorized users.

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A Reflexive Neural Network for Dynamic Biped Walking Control

Cited by 18 publications

References 28 publications

Exploiting the passive dynamics of a compliant leg to develop gait transitions

Exploiting the passive dynamics of a compliant leg to develop gait transitions

An Interactively Constrained Neuro-Evolution Approach for Behavior Control of Complex Robots

Bipedal robotic walking control derived from analysis of human locomotion

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