Feedback Control of an Exoskeleton for Paraplegics TOWARD ROBUSTLY STABLE, HANDS-FREE DYNAMIC WALKING

被引：87

作者：

Harib, Omar ^{[1
]}

Hereid, Ayonga ^{[2
]}

Agrawal, Ayush ^{[3
]}

Gurriet, Thomas ^{[4
]}

Finet, Sylvain ^{[5
]}

Boeris, Guilhem ^{[5
]}

Duburcq, Alexis ^{[6
]}

Mungai, M. Eva ^{[7
]}

Masselin, Matthieu ^{[8
]}

Ames, Aaron D. ^{[9
,10
,11
,12
,13
,14
]}

Sreenath, Koushil ^{[15
,16
,17
]}

Grizzle, Jessy W. ^{[18
,19
,20
]}

机构：

[1] Univ Michigan, Elect & Comp Engn, Ann Arbor, MI 48109 USA

[2] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA

[3] Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA

[4] CALTECH, Dept Mech & Civil Engn, Pasadena, CA 91125 USA

[5] Wandercraft, Paris, France

[6] Univ Dauphine, Robot & Comp Engn, Paris, France

[7] Univ Michigan, Mech Engn, Ann Arbor, MI 48109 USA

[8] Wandercraft, Developing Control Team, Paris, France

[9] CALTECH, Mech & Civil Engn, Pasadena, CA 91125 USA

[10] CALTECH, Control & Dynam Syst, Pasadena, CA 91125 USA

[11] Georgia Inst Technol, Woodruff Sch Mech Engn, Atlanta, GA 30332 USA

[12] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA

[13] CALTECH, Control & Dynam Syst, Pasadena, CA 91125 USA

[14] Texas A&M Univ, College Stn, TX USA

[15] Univ Calif Berkeley, Mech Engn, Berkeley, CA 94720 USA

[16] Univ Penn, GRASP Lab, Philadelphia, PA 19104 USA

[17] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA

[18] Univ Michigan, Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA

[19] Michigan Robot, Ann Arbor, MI USA

[20] IEEE, Piscataway, NJ USA

来源：

IEEE CONTROL SYSTEMS MAGAZINE | 2018年 / 38卷 / 06期

基金：

美国国家科学基金会;

关键词：

BIPEDAL ROBOTIC WALKING; OF-THE-ART; TRAJECTORY OPTIMIZATION; GAIT OPTIMIZATION; REHABILITATION; AMPUTATION; LOCOMOTION; STABILITY; ORTHOSES; AMPUTEES;

D O I：

10.1109/MCS.2018.2866604

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This article presents control of a high-degree-of-freedom, fully actuated lower-limb exoskeleton for paraplegic individuals. The key novelty is the ability for the user to walk without the use of crutches or other external means of stabilization. We harness the power of modern optimization techniques and supervised machine learning to develop a smooth feedback control policy that provides robust velocity regulation and perturbation rejection. Preliminary evaluation of the stability and robustness of the proposed approach is demonstrated through the Gazebo simulation environment. Additionally, preliminary experimental results with (complete) paraplegic individuals are included for the previous version of the controller.

引用

页码：61 / 87

页数：27

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