Objective: Active exoskeletons can handle different walking conditions, but require bulky components (e.g., motors) that need a significant source of power to do so. Purely passive exoskeletons are lightweight and energy-neutral, containing energy-recycling mechanisms that capture energy loss during negative power phases and return it as walking assistance. However, they are usually designed for stereotyped gaits (e.g., walking at fixed speed) and thus show poor adaptivity for variable conditions. This study is aimed to overcome these issues. Methods: A quasi-passive ankle exoskeleton is designed to integrate the merits of both active and passive exoskeletons, which captures the heel-strike energy loss and recycles it into propulsion. A novel, lightweight, energy-saving clutch and a heel-strike energy-storage mechanism are developed. They are coupled by a series spring that assists user's calf muscles. Six healthy subjects walked with the device on level ground and inclined surfaces to validate its functionality. Results: Level ground studies indicate that the energy-storage mechanism enhances the assistance by increasing the output torque of the exoskeleton. Reductions in metabolic cost (6.4 ± 1.3%, p < 0.05) were observed. During uphill walking, the assistance torque decreased compared with that on level ground, but it still reduced overall metabolic cost compared with baseline walking. During downhill walking, the assistance torque increased, but metabolic cost also slightly increased. Conclusion: These results demonstrate the functionality of the prototype on level ground and its limitations on inclined surfaces. Significance: The proposed device highlights the possibility of widening the potential applications of exoskeletons.

This paper carried out a series of designs, simulations and implementations by using the physical-like mechanism of a bionic quadruped robot dog as a vehicle. Through an investigation of the walking mechanisms of quadrupeds, a bionic structure is proposed that is capable of omnidirectional movements and smooth motions. Furthermore, the kinematic and inverse kinematic solutions based on the DH method are explored to lay the foundation for the gait algorithm. Afterward, a classical compound pendulum equation is applied as the foot-end trajectory and inverse kinematic solutions are combined to complete the gait planning. With appropriate foot–ground contact modeling, MATLAB and ADAMS are used to simulate the dynamic behavior and the diagonal trot gait of the quadruped robot. Finally, the physical prototype is constructed, designed and debugged, and its performance is measured through real-world experiments. Results show that the quadruped robot is able to balance itself during trot motion, for both its pitch and roll attitude. The goal of this work is to provide an affordable yet comprehensive platform for novice researchers in the field to study the dynamics, contact modeling, gait planning and attitude control of quadruped robots.

Over the past few decades, wearable exoskeletons of various forms have been developed to assist human activities or for rehabilitation of movement disorders. However, sustainable exoskeletons with efficient energy harvesting devices still have not been fully explored. In this paper, we propose the design of a lightweight wearable Bowden-cable-actuated soft exoskeleton robot with energy harvesting capability. Unlike previous wearable exoskeletons, the presented exoskeleton uses an electromagnetic generator to both harvest biomechanical energy and to output mechanical torque by controlling an operation mode relay switch based on a human’s gait. Moreover, the energy-harvesting module also acts as a knee impact absorber for the human, where the effective damping level can be modulated in a controlled manner. The harvested energy is regulated and stored in super capacitors for powering wireless sensory devices when needed. The experimental results show an average of a 7.91% reduction in thigh muscle activity, with a maximum of 3.2 W of electric power being generated during movement downstairs. The proposed design offers important prospects for the realization of lightweight wearable exoskeletons with improved efficiency and long-term sustainability.

In order to realize precise position tracking of a novel circular hydraulic actuator with parameter uncertainties and bounded disturbances, an adaptive sliding mode controller (ASMC) that incorporates a fuzzy tuning technique is proposed in this paper. The mechanical structure and basic principle of the actuator are first introduced, and the mathematical model of its corresponding valve-controlled hydraulic servo system is constructed. Based on Lyapunov stability theory, online parameter estimation and sliding mode controller design are effectively integrated to approximate the equivalent control of sliding mode. To mitigate the undesired chattering phenomenon and further improve system performance, a fuzzy tuning scheme is employed to regulate the proportional gain of the approaching control term. In addition, a real-time control platform is established, and the controllers parameter identification and position tracking are verified by preliminary experiments. Finally, the traditional PID controller and the exponent approaching sliding controller are also conduced to further evaluate the control performances of the designed controller, and the comparative results demonstrate that the proposed control scheme has better control performance in reducing errors for trajectory tracking.

Bowden-cable-actuated soft exoskeleton robots are known for their light weight and flexibility of power transmission during rehabilitation training or movement assistance for humans. However, friction-induced nonlinearity of the Bowden transmission cable and gearbox backlash pose great challenges forprecise tracking control of the exoskeleton robot. In this paper, we proposed the design of a learning-based repetitive controller which could compensate for the non-linearcable friction and gearbox backlash in an iterative manner. Unlike most of the previous control schemes, the presented controller does not require apriori knowledge or intensive modeling of the friction and backlash inside the exoskeleton transmission system. Instead, it uses the iterative learning control (ILC)to adaptively update the reference trajectory so that the output hysteresis caused by friction and backlashis minimized. In particular, a digital phase-lead compensator was designed and integrated with the ILC to address the issue of backlash delay and improve the stability and tracking performance. Experimental results showed an average of seven iterations for the convergence of learning and a 91.1% reduction in the RMS tracking error (~1.37 deg) compared with the conventional PD control. The proposed controller design offers promising options for the realization of lightweight, wearable exoskeletons with high tracking accuracies.