First Steps toward Automatically Generating Bipedal Robotic Walking from Human Data

Ames, Aaron D.

doi:10.1007/978-1-4471-2343-9_8

Cited by 54 publications

(124 citation statements)

References 21 publications

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“…Taking the coordinates θ = (θ 1 , θ 2 , θ 3 ) ∈ Θ as illustrated in Fig. 1, the method of Lagrange yields the equations of motion which can be easily rearranged into the form given in (1). (Note that u denotes the two input torques at the hips.)…”

Section: Clf's and Hybrid Systemsmentioning

confidence: 99%

“…In [17], [18], specially selected variables transverse to the zero dynamics manifold are Jacobian linearized and an exponentially stabilizing feedback is computed on the basis of LQR for periodic systems (see also [4] and [19]). In [2], [1], [14], [15], [26] (to only name a few), the transverse dynamics were input-output linearized and a high-gain time-invariant linear feedback was then employed; for example, when the outputs have vector relative degree 2, after creating a linear relationship between the inputs and outputs, the feedback is chosen to be…”

Section: Introductionmentioning

confidence: 99%

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Control lyapunov functions and hybrid zero dynamics

Ames

Galloway

Grizzle

2012

2012 IEEE 51st IEEE Conference on Decision and Control (CDC)

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115

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Abstract-Hybrid zero dynamics extends the Byrnes-Isidori notion of zero dynamics to a class of hybrid models called systems with impulse effects. Specifically, given a smooth submanifold that is contained in the zero set of an output function and is invariant under both the continuous flow of the system with impulse effects as well as its reset map, the restriction dynamics is called the hybrid zero dynamics. Prior results on the stabilization of periodic orbits of the hybrid zero dynamics have relied on input-output linearization of the transverse variables. The principal result of this paper shows how control Lyapunov functions can be used to exponentially stabilize periodic orbits of the hybrid zero dynamics, thereby significantly extending the class of stabilizing controllers. An illustration of this result on a model of a bipedal walking robot is provided.

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Section: Clf's and Hybrid Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Control lyapunov functions and hybrid zero dynamics

Ames

Galloway

Grizzle

2012

2012 IEEE 51st IEEE Conference on Decision and Control (CDC)

Self Cite

115

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“…In this paper, we use HumanInspired control [3], which aims for more human-like walking on bipedal robots [20,4]. Motion Transitions in this method [19] model the transition between two different modes, such as flat ground walking and stair climbing.…”

Section: Related Workmentioning

confidence: 99%

“…Previous work shows that the outputs of human locomotion can be expressed as either a linear function of time or a specific form termed the canonical walking function (CWF) [3,4,20],…”

Section: Definition 3 (Motion Parser)mentioning

confidence: 99%

“…The corresponding surface is referred to as the partial zero dynamics surface (PZ α ) and is fundamental to Human-Inspired Control. In [3], it was shown that stable walking can be achieved when the system operates on PZ α . The next step is to use optimization, imposing the constraints of hybrid zero dynamics, to find the parameters α * .…”

Section: Definition 3 (Motion Parser)mentioning

confidence: 99%

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Correct Software Synthesis for Stable Speed-Controlled Robotic Walking

Dantam¹,

Hereid²,

Ames³

et al. 2013

Robotics: Science and Systems IX

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Abstract-We present a software synthesis method for speedcontrolled robot walking based on supervisory control of a context-free Motion Grammar. First, we use Human-Inspired control to identify parameters for fixed speed walking and for transitions between fixed speeds, guaranteeing dynamic stability. Next, we build a Motion Grammar representing the discretetime control for this set of speeds. Then, we synthesize C code from this grammar and generate supervisors 1 online to achieve desired walking speeds, guaranteeing correctness of discrete computation. Finally, we demonstrate this approach on the Aldebaran NAO, showing stable walking transitions with dynamically selected speeds.

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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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First Steps toward Automatically Generating Bipedal Robotic Walking from Human Data

Cited by 54 publications

References 21 publications

Control lyapunov functions and hybrid zero dynamics

Control lyapunov functions and hybrid zero dynamics

Correct Software Synthesis for Stable Speed-Controlled Robotic Walking

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

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