Principles from human-human physical interaction may be necessary to design more intuitive and seamless robotic devices to aid human movement. Previous studies have shown that light touch can aid balance and that haptic communication can improve performance of physical tasks, but the effects of touch between two humans on walking balance has not been previously characterized. This study examines physical interaction between two persons when one person aids another in performing a beam-walking task. 12 pairs of healthy young adults held a force sensor with one hand while one person walked on a narrow balance beam (2 cm wide x 3.7 m long) and the other person walked overground by their side. We compare balance performance during partnered vs. solo beam-walking to examine the effects of haptic interaction, and we compare hand interaction mechanics during partnered beam-walking vs. overground walking to examine how the interaction aided balance. While holding the hand of a partner, participants were able to walk further on the beam without falling, reduce lateral sway, and decrease angular momentum in the frontal plane. We measured small hand force magnitudes (mean of 2.2 N laterally and 3.4 N vertically) that created opposing torque components about the beam axis and calculated the interactionmore »
This content will become publicly available on January 1, 2024
Optimal Energy Shaping Control for a Backdrivable Hip Exoskeleton
Task-dependent controllers widely used in exoskeletons track predefined trajectories, which overly constrain the volitional motion of individuals with remnant voluntary mobility. Energy shaping, on the other hand, provides task-invariant assistance by altering the human body's dynamic characteristics in the closed loop. While human-exoskeleton systems are often modeled using Euler-Lagrange equations, in our previous work we modeled the system as a port-controlled-Hamiltonian system, and a task-invariant controller was designed for a knee-ankle exoskeleton using interconnection-damping assignment passivity-based control. In this paper, we extend this framework to design a controller for a backdrivable hip exoskeleton to assist multiple tasks. A set of basis functions that contains information of kinematics is selected and corresponding coefficients are optimized, which allows the controller to provide torque that fits normative human torque for different activities of daily life. Human-subject experiments with two able-bodied subjects demonstrated the controller's capability to reduce muscle effort across different tasks.
- Award ID(s):
- 1949869
- Publication Date:
- NSF-PAR ID:
- 10401872
- Journal Name:
- Proceedings of the American Control Conference
- ISSN:
- 0743-1619
- Sponsoring Org:
- National Science Foundation
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In this work, we introduce a novel approach to assistive exoskeleton (or powered orthosis) control which avoids needing task and gait phase information. Our approach is based on directly designing the Hamiltonian dynamics of the target closed-loop behavior, shaping the energy of the human and the robot. Relative to previous energy shaping controllers for assistive exoskeletons, we introduce ground reaction force and torque information into the target behavior definition, reformulate the kinematics so as to avoid explicit matching conditions due to under-actuation, and avoid the need to switch between swing and stance energy shapes. Our controller introduces new states into the target Hamiltonian energy that represent a virtual second leg that is connected to the physical leg using virtual springs. The impulse the human imparts to the physical leg is amplified and applied to the virtual leg, but the ground reaction force acts only on the physical leg. A state transformation allows the proposed control to be available using only encoders, an IMU, and ground reaction force sensors. We prove that this controller is stable and passive when acted on by the ground reaction force and demonstrate the controller's strength amplifying behavior in a simulation. A linear analysis based onmore »
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Abstract Series elastic actuators (SEAs) are increasingly popular in wearable robotics due to their high fidelity closed-loop torque control capability. Therefore, it has become increasingly important to characterize its performance when used in dynamic environments. However, the conventional design approach does not fully capture the complexity of the entire exoskeleton system. These limitations stem from identifying design criteria with inadequate biomechanics data, utilizing an off-the-shelf user interface, and applying a benchtop-based proportional-integral-derivative control for actual low-level torque tracking. While this approach shows decent actuator performance, it does not consider human factors such as the dynamic back-driving nature of human-exoskeleton systems as well as soft human tissue dampening during the load transfer. Using holistic design guidelines to improve the SEA-based exoskeleton performance during dynamic locomotion, our final system has an overall mass of 4.8 kg (SEA mass of 1.1 kg) and can provide a peak joint torque of 108 Nm with a maximum velocity of 5.2 rad/s. Additionally, we present a user state-based feedforward controller to further improve the low-level torque tracking for diverse walking conditions. Our study results provide future exoskeleton designers with a foundation to further improve SEA-based exoskeleton’s torque tracking response for maximizing human-exoskeleton performance during dynamic locomotion.
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