The paper presents an angular velocity controller for the pneumatic soft robotic gloves which are applied to medical hand rehabilitation and performance augmentation. In order to configure the reliable control parameters, linear dynamic second-order state-space models of five robotic digits were identified by the experimental data. Using the identified models, proportional-integral (PI) control parameters were tuned by simulation studies. The tuned PI parameters were verified by experiment, which demonstrates that the system identification and simulation studies are reliable and can reduce the manual tuning time and prevent tuning hardware wear.

Microscale swimming robots have been envisaged for many biomedical applications such as targeted drug delivery, where the microrobot will be expected to navigate in a fluid environment while carrying a payload. We show that such a payload does not have to be physically bound to the swimmer, but may be instead manipulated by the microrobot through hydrodynamic interaction. We consider a magnetically actuated artificial microswimmer, whose locomotion induces a disturbance velocity field in the fluid, which moves a cargo particle in its vicinity. The problem investigated in this paper is therefore one of coupled locomotion-manipulation of two bodies in a fluid. The swimmer is actuated by a uniform, rotating magnetic field of constant strength leading to net motion in the direction perpendicular to the plane of rotation if the frequency associated with the periodic magnetic field is above a critical frequency. Below this critical frequency, the swimmer tumbles in place without net locomotion. Controlled motion of the particle and swimmer is achieved by switching the planes of rotation of the magnetic field and the frequency of the magnetic field above and below the critical frequency. The results of this paper show that microswimmers can be utilized as mobile manipulators of microparticles in a fluid.

Although soft robotic assistive gloves have high potential for restoring functional independence for individuals with motor impairment, their lack of rigid components makes it difficult to obtain accurate position sensing to validate their performance. To track soft device motion, standard practice relies on costly optical motion capture techniques, which have reduced accuracy due to limitations in marker occlusion and device deformation. We propose the Instrumented Hand as a low-cost, open-source measurement tool to serve as a standard solution for acquiring joint-level position and torque measurements from magnetoresistive sensors. Shown in a case study, the Instrumented Hand can be used to validate soft wearable devices and evaluate range of motion (ROM) and torque capabilities.