Haptic joysticks for man-machine interaction used in aerospace flight control have highly demanding requirements of reliability, force density, and high dynamics that can hardly be met with conventional electromagnetic actuators. This work explores the potential of using an alternative actuation strategy based on hyper-redundant MR clutches that modulate the force of a tendon-driven 2-degree-of-freedom spherical gimbal. A system design and its closed-loop force control scheme are proposed. Experimental results for an open-loop characterization, static force control and dynamic force control are set out and compared with typical requirements for such devices from the literature. Results show that the proposed architecture leads to one of the lightest systems reported in the literature that has the potential to meet reliability requirements by providing a jam-free design with duplex fault tolerance, and yet, can generate high force levels while providing enough force resolution. The approach is promising and can extend to high-performance collaborative robot applications.

Due to their relative ease of handling and low cost, inertial measurement unit (IMU)-based joint angle measurements are used for a widespread range of applications. These include sports performance, gait analysis, and rehabilitation (e.g., Parkinson's disease monitoring or poststroke assessment). However, a major downside of current algorithms, recomposing human kinematics from IMU data, is that they require calibration motions and/or the careful alignment of the IMUs with respect to the body segments. In this article, we propose a new method, which is alignment-free and self-calibrating using arbitrary movements of the user and an initial zero reference arm pose. The proposed method utilizes real-time optimization to identify the two dominant axes of rotation of the elbow joint. The performance of the algorithm was assessed in an optical motion capture laboratory. The estimated IMU-based angles of a human subject were compared to the ones from a marker-based optical tracking system. The self-calibration converged in under 9.5 s on average and the rms errors with respect to the optical reference system were 2.7° for the flexion/extension and 3.8° for the pronation/supination angle. Our method can be particularly useful in the field of rehabilitation, where precise manual sensor-to-segment alignment as well as precise, predefined calibration movements are impractical.