» Articles » PMID: 29104363

Towards Total Energy Shaping Control of Lower-Limb Exoskeletons

Overview
Date 2017 Nov 7
PMID 29104363
Citations 4
Authors
Affiliations
Soon will be listed here.
Abstract

Current robotic exoskeletons enforce fixed reference joint patterns during gait rehabilitation. These control methods aim to replicate normative joint kinematics but do not facilitate learning patient-specific kinematics. Trajectory-free control methods for exoskeletons are required to promote user control over joint kinematics. Our prior work on potential energy shaping provides virtual body-weight support through a trajectory-free control law, but altering only the gravitational forces does not assist the subject in accelerating/decelerating the body forward. Kinetic energy is velocity dependent and thus shaping the kinetic energy in addition to potential energy can yield greater dynamical changes in closed loop. In this paper, we generalize our previous work to achieve underactuated total energy shaping of the human body through a lower-limb exoskeleton. By shaping the fully-actuated part of the body's mass matrix, we satisfy the matching condition for different contact phases and obtain trajectory-free control laws. Simulations of a human-like biped demonstrate speed regulation in addition to body-weight support, indicating the potential clinical value of this control approach.

Citing Articles

Decentralized Passivity-Based Control With a Generalized Energy Storage Function for Robust Biped Locomotion.

Yeatman M, Lv G, Gregg R J Dyn Syst Meas Control. 2019; 141(10):1010071-10100711.

PMID: 31666751 PMC: 6611352. DOI: 10.1115/1.4043801.


On the Design and Control of Highly Backdrivable Lower-Limb Exoskeletons: A Discussion of Past and Ongoing Work.

Lv G, Zhu H, Gregg R IEEE Control Syst. 2019; 38(6):88-113.

PMID: 30598586 PMC: 6309856. DOI: 10.1109/MCS.2018.2866605.


Passivity-Based Control with a Generalized Energy Storage Function for Robust Walking of Biped Robots.

Yeatman M, Lv G, Gregg R Proc Am Control Conf. 2018; 2018:2958-2963.

PMID: 30220783 PMC: 6135528. DOI: 10.23919/ACC.2018.8431783.


Design and Validation of a Torque Dense, Highly Backdrivable Powered Knee-Ankle Orthosis.

Zhu H, Doan J, Stence C, Lv G, Elery T, Gregg R IEEE Int Conf Robot Autom. 2017; 2017:504-510.

PMID: 29057142 PMC: 5648365. DOI: 10.1109/ICRA.2017.7989063.

References
1.
Hornby T, Zemon D, Campbell D . Robotic-assisted, body-weight-supported treadmill training in individuals following motor incomplete spinal cord injury. Phys Ther. 2004; 85(1):52-66. View

2.
Vallery H, van Asseldonk E, Buss M, van der Kooij H . Reference trajectory generation for rehabilitation robots: complementary limb motion estimation. IEEE Trans Neural Syst Rehabil Eng. 2009; 17(1):23-30. DOI: 10.1109/TNSRE.2008.2008278. View

3.
Aguirre-Ollinger G, Colgate J, Peshkin M, Goswami A . Inertia compensation control of a one-degree-of-freedom exoskeleton for lower-limb assistance: initial experiments. IEEE Trans Neural Syst Rehabil Eng. 2012; 20(1):68-77. DOI: 10.1109/TNSRE.2011.2176960. View

4.
Gregg R, Dhaher Y, Degani A, Lynch K . On the mechanics of functional asymmetry in bipedal walking. IEEE Trans Biomed Eng. 2012; 59(5):1310-8. PMC: 4201655. DOI: 10.1109/TBME.2012.2186808. View

5.
Quintero H, Farris R, Hartigan C, Clesson I, Goldfarb M . A Powered Lower Limb Orthosis for Providing Legged Mobility in Paraplegic Individuals. Top Spinal Cord Inj Rehabil. 2012; 17(1):25-33. PMC: 3375739. DOI: 10.1310/sci1701-25. View