Simulating Prosthetic Gait ‐ Lessons to Learn

Brugger, Peter; Schmiedmayer, Heinz-Bodo

doi:10.1002/pamm.200310317

Cited by 4 publications

(2 citation statements)

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“…Moreover, achieving human‐like bipedal robotic locomotion can inversely help humans understand the human body in more depth. This understanding can be leveraged to build prosthetic devices for lower extremity amputees, which will help them walk with a gait as natural as a healthy human. Therefore, the important and far‐reaching ramifications of obtaining human‐like bipedal walking have attracted many researchers from a variety of fields of study.…”

Section: Introductionmentioning

confidence: 99%

Human‐inspired motion primitives and transitions for bipedal robotic locomotion in diverse terrain

Zhao

Powell

Ames

2013

Optim Control Appl Methods

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SUMMARYIn this paper, a control design approach is presented, which uses human data in the development of bipedal robotic control techniques for multiple locomotion behaviors. Insight into the fundamental behaviors of human locomotion is obtained through the examination of experimental human data for walking on flat ground, upstairs, and downstairs. Specifically, it is shown that certain outputs of the human, independent of locomotion terrain, can be characterized by a single function, termed the extended canonical human function. Through feedback linearization, human‐inspired locomotion controllers are leveraged to drive the outputs of the simulated robot, via the extended canonical human function, to the outputs from human locomotion. An optimization problem, subject to the constraints of partial hybrid zero dynamics, is presented that yields parameters of these controllers that provide the best fit to human data while ensuring stability of the controlled bipedal robot. The resulting behaviors are stable walking on flat ground, upstairs, and downstairs—these three locomotion modes are termed ‘motion primitives’. A second optimization is presented, which yields controllers that evolve the robot from one motion primitive to another—these modes of locomotion are termed ‘motion transitions’. A directed graph consisting these motion primitives and motion transitions has been constructed for the stable motion planning of bipedal locomotion. A final simulation is given, which shows the controlled evolution of a robotic biped as it transitions through each mode of locomotion over a pyramidal staircase. Copyright © 2013 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%

Human‐inspired motion primitives and transitions for bipedal robotic locomotion in diverse terrain

Zhao

Powell

Ames

2013

Optim Control Appl Methods

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“…One study [8] used the inverse-forward dynamics approach to investigate the interaction of the biomechanical system with other technical systems. This study validated the inclination that simulation can help in the design process.…”

Section: Introductionmentioning

confidence: 99%

Simulating prosthetic devices with human-inspired hybrid control

Sinnet

Zhao

Ames

2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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A method is proposed which enables testing of prosthetic devices in simulation. A hybrid model is used to represent human walking-the combination of continuous and discrete dynamics motivates the use of hybrid systems. A human walking experiment is analyzed and mathematical functions on the kinematics of the collected data are found which capture some of the fundamental behaviors associated with human walking. One model is considered in which these behaviors are fully tracked using feedback linearization; the intent of this is to simulate healthy human walking. Then, a second model is considered: this model is assumed to be a human with a transfemoral prosthesis; PD control is used on the prosthesis. All models considered demonstrate locally exponentially stable periodic orbits when simulated for four separate test subjects, or, in other words, the models exhibit stable walking even with a prosthetic lower extremity. The methods used in this paper are a stepping stone toward a process capable of rapidly prototyping potential prosthesis designs and controllers.

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