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The planar dual spring-loaded inverted pendulum (dual-SLIP) model is a well-established passive template of human walking on flat ground. This paper applies an actuated extension of the model to walking on inclines and declines to evaluate how well it captures the behavior observed in human slope walking. The motivation is to apply the template to improve control of humanoid robot walking and/or intent detection in exoskeleton-assisted walking. Gaits of the actuated planar dual-SLIP model are found via the solution of a constrained nonlinear optimization problem in ten parameters. The majority of those parameters define the actuation scheme that injects energy for incline walking and absorbs energy for decline walking to achieve periodic, nonconservative gaits. Solution gaits across the speed range of 1.0 to 1.6 ms and slope range of −10 to 10 degrees exhibit some of the characteristics of human walking, such as the effect of slope on stance duration, step frequency, and step length. Efforts to reduce the number of parameters optimized by enforcing relationships observed in the solution gaits proved unsuccessful, suggesting that future work must trade off model complexity with fidelity of representation of human behavior.
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This content will become publicly available on November 15, 2025
Natural variability and individuality of walking behavior in Drosophila
ABSTRACT Insects use walking behavior in a large number of contexts, such as exploration, foraging, escape and pursuit, or migration. A lot is known about how nervous systems produce this behavior in general and also how certain parameters vary with regard to walking direction or speed, for instance. An aspect that has not received much attention is whether and how walking behavior varies across individuals of a particular species. To address this, we created a large corpus of kinematic walking data of many individuals of the fruit fly Drosophila. We only selected instances of straight walking in a narrow range of walking speeds to minimize the influence of high-level parameters, such as turning and walking speed, aiming to uncover more subtle aspects of variability. Using high-speed videography and automated annotation, we captured the positions of the six leg tips for thousands of steps and used principal components analysis to characterize the postural space individuals used during walking. Our analysis shows that the largest part of walking kinematics can be described by five principal components (PCs). Separation of these five PCs into a 2D and a 3D subspace divided the description of walking behavior into invariant features shared across individuals and features that relate to the specifics of individuals; the latter features can be regarded as idiosyncrasies. We also demonstrate that this approach can detect the effects of experimental interventions in an unbiased manner and that general aspects of individuality, such as the individual walking posture, can be described.
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- Award ID(s):
- 2015317
- PAR ID:
- 10627456
- Publisher / Repository:
- The Company of Biologists
- Date Published:
- Journal Name:
- Journal of Experimental Biology
- Volume:
- 227
- Issue:
- 22
- ISSN:
- 0022-0949
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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