While wearable robots that utilize intrinsically soft materials for actuation offer enhanced safety and biological compatibility, the challenges of sensing and control significantly affect their performance. The control problem in such systems is inherently complex, and the inclusion of 'softness' introduces additional nonlinearities, hysteresis, and uncertainties. Furthermore, the effectiveness of control strategies is highly dependent on sensor selection and integration, which presents its own challenges. Most robotic systems require separate sensors for control purposes. In this study, a new sensing and control scheme are introduced for soft wearable robots, leveraging the intrinsic soft-sensing capability of fluidic filament actuators without adding computational complexity. This method enables simultaneous sensing and actuation with$\mathbf{9 6 \%}$position accuracy, even under physical disturbances. This approach is demonstrated with a soft assistive device for elbow flexion/extension, achieving 70.5% tracking accuracy and a 0.09s response delay to human intention, ensuring the system provides minimal resistance when assistance is not needed, while delivering the required support when necessary.

Aneurysms, balloon-like bulges in blood vessels, present a significant health risk due to their potential to rupture, leading to life-threatening internal bleeding. Current treatments often involve delivering embolic materials or metal coils to fill these bulges, occluding them from the pressure of blood flow. However, clinical micro-catheters that deploy embolic materials used today face limitations, primarily their rigidity and the lack of active control over the bending tip of the catheter. This paper introduces a new soft micro-robotics catheter, with diameter of only 0.8 mm, equipped with a hollow channel. With this new design, the new device can induce bending motions at its tip for active steerability to reach desired aneurysm targets and then perform the delivery of embolic materials and tools. To enhance the control and precise navigation during procedures, a robust mathematical model and image processing techniques are also introduced and validated. Experiments are also performed to characterise and validate the model’s accuracy and the steerability and navigation capabilities of the new micro-catheter.

Physically assistance robots have been conceptualized to compensate or augment the human musculoskeletal function. However, due to the concerns of safety and effectiveness for physical human-robot interaction (pHRI) in such robots, compliant joints are preferred over the rigid joints. This paper illustrates the implementation of admittance control in a sit-to-stand (STS) assistance robot. The 3-degrees of freedom (dof) robot comprises of ball screw-based linear actuators that are arranged in a parallel configuration. While the actuation system is preferable for strength and performance, the non-backdrivable characteristic corroborates the rigidity of the joint, making it unfavorable for human-robot interaction operation. To enhance compliance, force sensor-based admittance control system is implemented. Regarding motion planning, the trajectory were modeled as Dynamic Movement Primitives (DMP), which facilitates the implementation of admittance control. The proposed model is implemented in the robot prototype and validated by illustrating the force input and the motion output.