Powered exoskeletons need actuators that are lightweight, compact, and efficient while allowing for accurate torque control. To satisfy these requirements, researchers have proposed using series elastic actuators (SEAs). SEAs use a spring in series with rotary or linear actuators. The spring compliance, in conjunction with an appropriate control scheme, improves torque control, efficiency, output impedance, and disturbance rejection. However, springs add weight to the actuator and complexity to the control, which may have negative effects on the performance of the powered exoskeleton. Therefore, there is an unmet need for new SEA designs that are lighter and more efficient than available systems, as well as for control strategies that push the performance of SEA-based exoskeletons without requiring complex modeling and tuning. This article presents the design, development, and testing of a novel SEA with high force density for powered exoskeletons, as well as the use of a two degree-of-freedom (2DOF) PID system to improve output impedance and disturbance rejection. Benchtop testing results show reduced output impedance and damping values when using a 2DOF PID controller as compared to a 1DOF PID controller. Human experiments with three able-bodied subjects (N = 3) show improved torque tracking with reduced root-mean-square error by 45.2% and reduced peak error by 49.8% when using a 2DOF PID controller. Furthermore, EMG data shows a reduction in peak EMG value when using the exoskeleton in assistive mode compared to the exoskeleton operating in transparent mode.

The energetic advantages of series and parallel elastic actuators have been characterized in the literature considering different elastic systems and different tasks. These characterizations usually determine the energy consumption of a specific system during a specific task and generalize poorly. This paper proposes an energetic characterization of elastic actuators, following an analytical approach, rather than a data-driven one. In particular, this work analyzes the energy consumption of elastic actuators during resonant motion and introduces a novel efficiency index. This index characterizes energy consumption as a function of inherent actuator parameters only, generalizing over the specific tasks. The proposed analysis is validated using simulations and experiments, demonstrating its coherence with analytical results.

In this work we present NEUROExos, a novel generation of upper-limb exoskeletons developed in recent years at The BioRobotics Institute of Scuola Superiore Sant’Anna (Italy). Specifically, we present our attempts to progressively (i) improve the ergonomics and safety (ii) reduce the encumbrance and weight, and (iii) develop more intuitive human–robot cognitive interfaces. Our latest prototype, described here for the first time, extends the field of application to assistance in activities of daily living, thanks to its compact and portable design. The experimental studies carried out on these devices are summarized, and a perspective on future developments is presented.

Force-controlled series elastic actuators (SEAs) are the widely used components of novel physical human–robot interaction applications such as assistive and rehabilitation robotics. These systems are characterized by the presence of the “human in the loop” so that control response and stability depend on uncertain human dynamics. A common approach to guarantee stability is to use a passivity-based controller. Unfortunately, existing passivity-based controllers for SEAs do not define the performance of the force/torque loop. We propose a method to obtain predictable force/torque dynamics based on adaptive control and oversimplified human models. We propose a class of stable human-adaptive algorithms and experimentally show advantages of the proposed approach.