Orthotic Body-Weight Support Through Underactuated Potential Energy Shaping with Contact Constraints

Decentralized Passivity-Based Control With a Generalized Energy Storage Function for Robust Biped Locomotion

This paper details a decentralized passivity-based control (PBC) to improve the robustness of biped locomotion in the presence of gait-generating external torques and parametric errors in the biped model. Previous work demonstrated a passive output for biped systems based on a generalized energy that, when directly used for feedback control, increases the basin of attraction and convergence rate of the biped to a stable limit cycle. This paper extends the concept with a theoretical framework to address both uncertainty in the biped model and a lack of sensing hardware, by allowing the designer to neglect arbitrary states and parameters in the system. This framework also allows the control to be implemented on wearable devices, such as a lower limb exoskeleton or powered prosthesis, without needing a model of the user's dynamics. Simulations on a six-link biped model demonstrate that the proposed control scheme increases the convergence rate of the biped to a walking gait and improves the robustness to perturbations and to changes in ground slope.

Passivity-Based Control with a Generalized Energy Storage Function for Robust Walking of Biped Robots

This paper offers a novel generalization of a passivity-based, energy tracking controller for robust bipedal walking. Past work has shown that a biped limit cycle with a known, constant mechanical energy can be made robust to uneven terrains and disturbances by actively driving energy to that reference. However, the assumption of a known, constant mechanical energy has limited application of this passivity-based method to simple toy models (often passive walkers). The method presented in this paper allows the passivity-based controller to be used in combination with an arbitrary inner-loop control that creates a limit cycle with a constant generalized system energy. We also show that the proposed control method accommodates arbitrary degrees of underactuation. Simulations on a 7-link biped model demonstrate that the proposed control scheme enlarges the basin of attraction, increases the convergence rate to the limit cycle, and improves robustness to ground slopes.

Underactuated Potential Energy Shaping with Contact Constraints: Application to a Powered Knee-Ankle Orthosis

Body-weight support (i.e., gravity compensation) is an effective clinical tool for gait rehabilitation after neurological impairment. Body-weight supported training systems have been developed to help patients regain mobility and confidence during walking, but conventional systems constrain the patient's treatment in clinical environments. We propose that this challenge could be addressed by virtually providing patients with bodyweight support through the actuators of a powered orthosis (or exoskeleton) utilizing potential energy shaping control. However, the changing contact conditions and degrees of underactuation encountered during human walking present significant challenges to consistently matching a desired potential energy for the human in closed loop. We therefore derive a generalized matching condition for shaping Lagrangian systems with holonomic contact constraints. By satisfying this matching condition for four phases of gait, we derive passivity-based control laws to achieve virtual body-weight support through a powered knee-ankle orthosis. We demonstrate beneficial effects of virtual body-weight support in simulations of a human-like biped model, indicating the potential clinical value of this proposed control approach.

Towards Total Energy Shaping Control of Lower-Limb Exoskeletons

Current robotic exoskeletons enforce fixed reference joint patterns during gait rehabilitation. These control methods aim to replicate normative joint kinematics but do not facilitate learning patient-specific kinematics. Trajectory-free control methods for exoskeletons are required to promote user control over joint kinematics. Our prior work on potential energy shaping provides virtual body-weight support through a trajectory-free control law, but altering only the gravitational forces does not assist the subject in accelerating/decelerating the body forward. Kinetic energy is velocity dependent and thus shaping the kinetic energy in addition to potential energy can yield greater dynamical changes in closed loop. In this paper, we generalize our previous work to achieve underactuated total energy shaping of the human body through a lower-limb exoskeleton. By shaping the fully-actuated part of the body's mass matrix, we satisfy the matching condition for different contact phases and obtain trajectory-free control laws. Simulations of a human-like biped demonstrate speed regulation in addition to body-weight support, indicating the potential clinical value of this control approach.

Design and Validation of a Torque Dense, Highly Backdrivable Powered Knee-Ankle Orthosis

This paper presents the mechatronic design and experimental validation of a novel powered knee-ankle orthosis for testing torque-driven rehabilitation control strategies. The modular actuator of the orthosis is designed with a torque dense motor and a custom low-ratio transmission (24:1) to provide mechanical transparency to the user, allowing them to actively contribute to their joint kinematics during gait training. The 4.88 kg orthosis utilizes frameless components and light materials, such as aluminum alloy and carbon fiber, to reduce its mass. A human subject experiment demonstrates accurate torque control with high output torque during stance and low backdrive torque during swing at fast walking speeds. This work shows that backdrivability, precise torque control, high torque output, and light weight can be achieved in a powered orthosis without the high cost and complexity of variable transmissions, clutches, and/or series elastic components.

Prosthetic Leg Control in the Nullspace of Human Interaction

Recent work has extended the control method of virtual constraints, originally developed for autonomous walking robots, to powered prosthetic legs for lower-limb amputees. Virtual constraints define desired joint patterns as functions of a mechanical phasing variable, which are typically enforced by torque control laws that linearize the output dynamics associated with the virtual constraints. However, the output dynamics of a powered prosthetic leg generally depend on the human interaction forces, which must be measured and canceled by the feedback linearizing control law. This feedback requires expensive multi-axis load cells, and actively canceling the interaction forces may minimize the human's influence over the prosthesis. To address these limitations, this paper proposes a method for projecting virtual constraints into the nullspace of the human interaction terms in the output dynamics. The projected virtual constraints naturally render the output dynamics invariant with respect to the human interaction forces, which instead enter into the internal dynamics of the partially linearized prosthetic system. This method is illustrated with simulations of a transfemoral amputee model walking with a powered knee-ankle prosthesis that is controlled via virtual constraints with and without the proposed projection.

A Control Framework for Anthropomorphic Biped Walking Based on Stabilizing Feedforward Trajectories

Although dynamic walking methods have had notable successes in control of bipedal robots in the recent years, still most of the humanoid robots rely on quasi-static Zero Moment Point controllers. This work is an attempt to design a highly stable controller for dynamic walking of a human-like model which can be used both for control of humanoid robots and prosthetic legs. The method is based on using time-based trajectories that can induce a highly stable limit cycle to the bipedal robot. The time-based nature of the controller motivates its use to entrain a model of an amputee walking, which can potentially lead to a better coordination of the interaction between the prosthesis and the human. The simulations demonstrate the stability of the controller and its robustness against external perturbations.

A Robust Parameterization of Human Gait Patterns Across Phase-Shifting Perturbations

The phase of human gait is difficult to quantify accurately in the presence of disturbances. In contrast, recent bipedal robots use time-independent controllers relying on a mechanical phase variable to synchronize joint patterns through the gait cycle. This concept has inspired studies to determine if human joint patterns can also be parameterized by a mechanical variable. Although many phase variable candidates have been proposed, it remains unclear which, if any, provide a robust representation of phase for human gait analysis or control. In this paper we analytically derive an ideal phase variable (the hip phase angle) that is provably monotonic and bounded throughout the gait cycle. To examine the robustness of this phase variable, ten able-bodied human subjects walked over a platform that randomly applied phase-shifting perturbations to the stance leg. A statistical analysis found the correlations between nominal and perturbed joint trajectories to be significantly greater when parameterized by the hip phase angle (0.95+) than by time or a different phase variable. The hip phase angle also best parameterized the transient errors about the nominal periodic orbit. Finally, interlimb phasing was best explained by local (ipsilateral) hip phase angles that are synchronized during the double-support period.

Experimental Implementation of Underactuated Potential Energy Shaping on a Powered Ankle-Foot Orthosis

Traditional control methodologies of rehabilitation orthoses/exoskeletons aim at replicating normal kinematics and thus fall into the category of kinematic control. This control paradigm depends on pre-defined reference trajectories, which can be difficult to adjust between different locomotor tasks and human subjects. An alternative control category, kinetic control, enforces kinetic goals (e.g., torques or energy) instead of kinematic trajectories, which could provide a flexible learning environment for the user while freeing up therapists to make corrections. We propose that the theory of underactuated potential energy shaping, which falls into the category of kinetic control, could be used to generate virtual body-weight support for stroke gait rehabilitation. After deriving the nonlinear control law and simulating it on a human-like biped model, we implemented this controller on a powered ankle-foot orthosis that was designed specifically for testing torque control strategies. Experimental results with an able-bodied human subject demonstrate the feasibility of the control approach for both positive and negative virtual body-weight augmentation.