Literature DB >> 21555844

Running over unknown rough terrain with a one-legged planar robot.

Ben Andrews1, Bruce Miller, John Schmitt, Jonathan E Clark.   

Abstract

The ability to traverse unknown, rough terrain is an advantage that legged locomoters have over their wheeled counterparts. However, due to the complexity of multi-legged systems, research in legged robotics has not yet been able to reproduce the agility found in the animal kingdom. In an effort to reduce the complexity of the problem, researchers have developed single-legged models to gain insight into the fundamental dynamics of legged running. Inspired by studies of animal locomotion, researchers have proposed numerous control strategies to achieve stable, one-legged running over unknown, rough terrain. One such control strategy incorporates energy variations into the system during the stance phase by changing the force-free leg length as a sinusoidal function of time. In this research, a one-legged planar robot capable of implementing this and other state-of-the-art control strategies was designed and built. Both simulated and experimental results were used to determine and compare the stability of the proposed controllers as the robot was subjected to unknown drop and raised step perturbations equal to 25% of the nominal leg length. This study illustrates the relative advantages of utilizing a minimal-sensing, active energy removal control scheme to stabilize running over rough terrain.

Mesh:

Year:  2011        PMID: 21555844     DOI: 10.1088/1748-3182/6/2/026009

Source DB:  PubMed          Journal:  Bioinspir Biomim        ISSN: 1748-3182            Impact factor:   2.956


  3 in total

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Authors:  M Calisti; G Picardi; C Laschi
Journal:  J R Soc Interface       Date:  2017-05       Impact factor: 4.118

2.  Swing-leg trajectory of running guinea fowl suggests task-level priority of force regulation rather than disturbance rejection.

Authors:  Yvonne Blum; Hamid R Vejdani; Aleksandra V Birn-Jeffery; Christian M Hubicki; Jonathan W Hurst; Monica A Daley
Journal:  PLoS One       Date:  2014-06-30       Impact factor: 3.240

3.  Biped Walking Based on Stiffness Optimization and Hierarchical Quadratic Programming.

Authors:  Xuanyang Shi; Junyao Gao; Yizhou Lu; Dingkui Tian; Yi Liu
Journal:  Sensors (Basel)       Date:  2021-03-02       Impact factor: 3.576

  3 in total

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