Rehabilitative robotics, particularly lower-limb exoskeletons (LLEs), have gained increasing importance in aiding patients regain ambulatory functions. One of the challenges in making these systems effective is the implementation of an assist-as-needed (AAN) control strategy that intervenes only when the patient deviates from the correct movement pattern. Equally crucial is the need for the LLE to exhibit "transparency" — minimising its interaction forces with the wearer to feel as natural as possible. This paper introduces a novel approach to transparency control based on a human-in-the-loop velocity optimisation framework. The proposed method employs torque data captured from past steps through a Series Elastic Actuator (SEA) to approximate the wearer’s intended future movements and computes a corresponding transparent velocity trajectory. The velocity commands are complemented by an Adaptive Frequency Oscillator (AFO) based position controller that leverages the periodic nature of human gait and is modified with a force sensor for increased reactiveness to human gait variations. This approach is experimentally evaluated against a standard zero-torque controller with a stationary single-degree-of-freedom knee exoskeleton test platform in a proof-of-concept study. Preliminary results indicate that combining adaptive oscillators with interaction force sensing can improve transparency compared to the conventional zero-torque controller, using force readings for position control and torque measurements for velocity optimisation and control.

Modern collaborative robotic applications require robot motions that are predictable for human coworkers. Therefore, trajectories often need to be planned in task space rather than configuration space ($\mathcal{C}$-space). While the interpolation of translations in Euclidean space is straightforward, the interpolation of rotations in$SO(3)$is more complex. Most approaches originating from computer graphics do not exhibit the often desired$\mathcal{C}^{2}$-continuity in robotics. Our main contribution is a$\mathcal{C}^{2}$-continuous, zero-clamped interpolation scheme for quaternions that computes a fast synchronized motion given a set of waypoints. As a second contribution, we present modifications to two state-of-the-art quaternion interpolation schemes, Spherical Quadrangle Interpolation (SQUAD) and Spherical Parabolic Blends (SPB), to enable them to compute$\mathcal{C}^{2}$-continuous, zero-clamped trajectories. In experiments, we demonstrate that for the time optimization of trajectories, our approach is computationally efficient and at the same time computes smooth trajectory profiles.