Haptic Transparency and Interaction Force Control for a Lower-Limb Exoskeleton

TL;DR

This work tackles the problem of achieving haptic transparency and precise interaction-torque control for floating-base lower-limb exoskeletons during overground walking. It introduces WECC, a whole-exoskeleton closed-loop compensation framework that combines a continuous whole-body dynamic model with joint-torque measurements and a constrained optimization-based controller to track desired interaction torques while respecting physical and safety limits. The method is evaluated on three subjects against a simplified double-pendulum controller and a no-drive baseline, showing consistent interaction-torque tracking across the gait cycle and superior stance-phase performance for WECC. The results highlight WECC’s potential to enable natural haptic reinforcement modalities (assist-as-needed, resistive, and error augmentation) in overground rehabilitation and daily use, especially for heavy exoskeletons where full-body dynamics are essential for accurate force control.

Abstract

Controlling the interaction forces between a human and an exoskeleton is crucial for providing transparency or adjusting assistance or resistance levels. However, it is an open problem to control the interaction forces of lower-limb exoskeletons designed for unrestricted overground walking. For these types of exoskeletons, it is challenging to implement force/torque sensors at every contact between the user and the exoskeleton for direct force measurement. Moreover, it is important to compensate for the exoskeleton's whole-body gravitational and dynamical forces, especially for heavy lower-limb exoskeletons. Previous works either simplified the dynamic model by treating the legs as independent double pendulums, or they did not close the loop with interaction force feedback. The proposed whole-exoskeleton closed-loop compensation (WECC) method calculates the interaction torques during the complete gait cycle by using whole-body dynamics and joint torque measurements on a hip-knee exoskeleton. Furthermore, it uses a constrained optimization scheme to track desired interaction torques in a closed loop while considering physical and safety constraints. We evaluated the haptic transparency and dynamic interaction torque tracking of WECC control on three subjects. We also compared the performance of WECC with a controller based on a simplified dynamic model and a passive version of the exoskeleton. The WECC controller results in a consistently low absolute interaction torque error during the whole gait cycle for both zero and nonzero desired interaction torques. In contrast, the simplified controller yields poor performance in tracking desired interaction torques during the stance phase.

Figures (13)

• Figure 1: ExoMotus-X2 lower-limb exoskeleton, featuring a close-up view of the strain gauge implementation (left) and a user wearing the exoskeleton (right).
• Figure 2: State machine structure of the gait states. The variables ${F_{\text{l}}}$ and ${F_{\text{r}}}$ are the left foot and right foot vertical force readings, respectively. The threshold force that triggers state change is represented by $F_{\text{lim}}$. This threshold can be an absolute force value or a ratio of the total vertical forces.When this state machine is used in real-time control, states are not allowed to change more than once every 150 ms for robustness to noise. During walking, the focus of this paper, the flight state never occurs.
• Figure 3: Different gait states and representation of the generalized coordinates. Whole-body model representations are shown in sub-figures (a), (b), and (c). Sub-figure (d) corresponds to the stance and swing phases of the simplified model.
• Figure 4: Schematic of the interaction force controller.
• Figure 5: Interaction torques between the human and exoskeleton during transparency trials. The figures on the top row show the interaction torques vs. normalized gait duration for a representative subject. The data includes every step of both legs, and the shaded area represents $\pm$ standard deviation. On the bottom row, the box and whisker plots of the mean absolute interaction torques during the stance phase, swing phase, and the whole gait cycle are presented. Mean absolute values of the corresponding phase at each step of both legs of all three subjects are used as a data point after removing the inter-subject variability in box and whisker plots ($N \approx 320$). *** indicates $p < 0.001$ from Tukey's HSD test.