Year: 2026
Type: article
Abstract: Tendon-driven continuum actuators (TDCAs) provide compliant and lifelike motion that is well suited for human-robot interaction, but their structural compliance and underactuation make them susceptible to undesired vibrations, particularly along unactuated axes under load. This work addresses vibration suppression in such systems by proposing a real-time control strategy for a two-degree-of-freedom TDCA-based soft robotic neck used in the HARU social robot, where yaw motion is unactuated and prone to oscillations due to eccentric loading. The proposed approach combines a current-based tendon pretensioning routine, baseline PID control of the actuated pitch and roll axes, and a novel Coupled Axis Indirect Vibration Suppression (CIVS) mechanism. CIVS exploits mechanical cross-axis coupling by using high-pass filtered yaw acceleration from an inertial sensor to generate transient tension modulations in the actuated tendons, thereby increasing effective damping of the unactuated yaw mode without introducing additional hardware or compromising compliance. A classical sliding mode control is also implemented as a nonlinear benchmark under identical hardware constraints. Experimental validation on the HARU neck under representative loading conditions demonstrates that the proposed method achieves substantial vibration attenuation. Compared to the baseline controller, CIVS reduces yaw angular range by approximately 53% and yaw acceleration area by over 60%, while preserving smooth, expressive motion. The results further show that CIVS outperforms the sliding mode controller in suppressing vibrations on the unactuated axis. These findings indicate that indirect, feedback-driven tendon modulation provides an effective and low-complexity solution for mitigating load-induced vibrations in underactuated soft robotic systems, making the approach particularly suitable for interactive applications where safety, compliance, and motion expressivity are critical.
Source: Frontiers in Robotics and AI
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W7125384629