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Energy shaping methods can be used to design task-invariant feedback control laws for the powered exoskeletons (i.e., orthoses). In order to achieve a desired closed-loop energy, certain matching conditions must be satisfied, which are sets of nonlinear partial differential equations. In this paper, we solve the matching conditions and come up with a new solution for under-actuated systems by using Auckly’s method.We find a unified feedback control law that is task-invariant with respect to human inputs and different contact conditions. We propose assistive and resistive shaping strategies to alter the mass/inertia matrix and simulate on a powered knee-ankle exoskeleton. The simulation results show the reduction and increment of the human model’s metabolic cost of generating muscular forces in human walking. The interchange between the kinetic and potential energy and the changes in acceleration of the center of mass are also investigated in the simulation.
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Pushing revisited: Differential flatness, trajectory planning, and stabilization
We prove that quasi-static pushing with a sticking contact and ellipsoid approximation of the limit surface is differential flat. Both graphical and algebraic derivations are given. A major conclusion is that the pusher–slider system is reducible to the Dubins car problem where the sticking contact constraints translate to bounded curvature. Planning is as easy as computing a Dubins curve with the additional benefit of time-optimality. For trajectory stabilization, we design closed-loop control using dynamic feedback linearization or open-loop control using two contact points as a form of mechanical feedback. We conduct robotic experiments using objects with different pressure distributions, shape, and contact materials placed at different initial poses that require difficult switching action maneuvers to the goal pose. The average error is within 1.67 mm in translation and 0.5° in orientation over 60 experimental trials. We also show an example of pushing among obstacles using a RRT planner with exact steering.
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- Award ID(s):
- 1637908
- PAR ID:
- 10546986
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- The International Journal of Robotics Research
- Volume:
- 38
- Issue:
- 12-13
- ISSN:
- 0278-3649
- Format(s):
- Medium: X Size: p. 1477-1489
- Size(s):
- p. 1477-1489
- Sponsoring Org:
- National Science Foundation
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