Bioinspired legged locomotion comprises different aspects, such as (i) benefiting from reduced complexity control approaches as observed in humans/animals, (ii) combining embodiment with the controllers and (iii) reflecting neural control mechanisms. One of the most important lessons learned from nature is the significant role of compliance in simplifying control, enhancing energy efficiency and robustness against perturbations for legged locomotion. In this research, we investigate how body morphology in combination with actuator design may facilitate motor control of leg function. Inspired by the human leg muscular system, we show that biarticular muscles have a key role in balancing the upper body, joint coordination and swing leg control. Appropriate adjustment of biarticular spring rest length and stiffness can simplify the control and also reduce energy consumption. In order to test these findings, the BioBiped3 robot was developed as a new version of BioBiped series of biologically inspired, compliant musculoskeletal robots. In this robot, three-segmented legs actuated by mono- and biarticular series elastic actuators mimic the nine major human leg muscle groups. With the new biarticular actuators in BioBiped3, novel simplified control concepts for postural balance and for joint coordination in rebounding movements (drop jumps) were demonstrated and approved.

The amount of research on developing exoskeletons for human gait assistance has been growing in the recent years. However, the control design of exoskeletons for assisting human walking remains unclear. This paper presents a novel bio-inspired reflex-based control for assisting human walking. In this approach, the leg force is used as a feedback signal to adjust hip compliance. The effects of modulating hip compliance on walking gait is investigated through joint kinematics, leg muscle activations and overall metabolic costs for eight healthy young subjects. Reduction in the average metabolic cost and muscle activation are achieved with fixed hip compliance. Compared to the fixed hip compliance, improved assistance as reflected in more consistent reduction in muscle activities and more natural kinematic behaviour are obtained using the leg force feedback. Furthermore, smoother motor torques and less peak power are two additional advantages obtained by compliance modulation. The results show that the proposed control method which is inspired by human posture control can not only facilitate the human gait, but also reduce the exoskeleton power consumption. This demonstrates that the proposed bio-inspired controller allows a synergistic interaction between human and robot.

A better understanding of how actuator design supports locomotor function may help develop novel and more functional powered assistive devices or robotic legged systems. Legged robots comprise passive parts (e.g., segments, joints and connections) which are moved in a coordinated manner by actuators. In this study, we propose a novel concept of a hybrid electric-pneumatic actuator (EPA) as an enhanced variable impedance actuator (VIA). EPA is consisted of a pneumatic artificial muscle (PAM) and an electric motor (EM). In contrast to other VIAs, the pneumatic artificial muscle (PAM) within the EPA provides not only adaptable compliance, but also an additional powerful actuator with muscle-like properties, which can be arranged in different combinations (e.g., in series or parallel) to the EM. The novel hybrid actuator shares the advantages of both integrated actuator types combining precise control of EM with compliant energy storage of PAM, which are required for efficient and adjustable locomotion. Experimental and simulation results based on the new dynamic model of PAM support the hypothesis that combination of the two actuators can improve efficiency (energy and peak power) and performance, while does not increase control complexity and weight, considerably. Finally, the experiments on EPA adapted bipedal robot (knee joint of the BioBiped3 robot) show improved efficiency of the actuator at different frequencies.

This paper proposes a methodology to reconstruct the vertical GRFs from the registered body motion that is reasonably robust against measurement noise. The vertical GRFs are reconstructed from the experimentally identified time-variant pacing rate and a generalised single-step load model available in the literature. The proposed methodology only requires accurately capturing the body motion within the frequency range 1–10 Hz and does not rely on the exact magnitude of the registered signal. The methodology can therefore also be applied when low-cost sensors are used and to minimize the impact of soft-tissue artefacts. In addition, the proposed procedure can be applied regardless of the position of the sensor on the human body, as long as the recorded body motion allows for identifying the time of a nominally identical event in successive walking cycles. The methodology is illustrated by a numerical example and applied to an experimental dataset where the ground reaction forces and the body motion were registered simultaneously. The results show that the proposed methodology allows for arriving at a good estimate of the vertical ground reaction forces. When the impact of soft-tissue artefacts is low, a comparable estimate can be obtained using Newton’s second law of motion.

It has been shown that human-like hopping can be achieved by muscle reflex control in neuromechanical simulations. However, it is unclear if this concept is applicable and feasible for controlling a real robot. This paper presents a low-cost two-segmented robotic leg design and demonstrates the feasibility and the benefits of the bio-inspired neuromuscular reflex based control for hopping. Simulation models were developed to describe the dynamics of the real robot. Different neuromuscular reflex pathways were investigated with the simulation models. We found that stable hopping can be achieved with both positive muscle force and length feedback, and the hopping height can be controlled by modulating the muscle force feedback gains with the return maps. The force feedback neuromuscular reflex based controller is robust against body mass and ground impedance changes. Finally, we implemented the controller on the real robot to prove the feasibility of the proposed neuromuscular reflex based control idea. This paper demonstrates the neuromuscular reflex based control approach is feasible to implement and capable of achieving stable and robust hopping in a real robot. It provides a promising direction of controlling the legged robot to achieve robust dynamic motion in the future.

Cycling stands as one of the most widely embraced leisure activities and serves purposes such as exercise, rehabilitation, and commuting. This study aimed to assess the feasibility of assisting three unimpaired participants (age: 34.0 ± 7.9 years, height: 1.86 ± 0.02 m, weight: 75.7 ± 12.7 kg) using the GuroX hip exoskeleton, originally designed for walking assistance, during cycling against a resistance of 1 W/kg. The performance evaluation employed a sweep protocol that manipulated the timing of the exoskeleton’s peak extension and flexion torque in addition to human-in-the-loop optimization to enhance these timings based on metabolic cost. Our findings indicate that with a peak assistance torque of approximately 10.3 Nm for extension and flexion, the GuroX substantially reduced the net metabolic cost of cycling by 31.4 ± 8.1% and 26.4 ± 14.1% compared to transparent and without exoskeleton conditions, respectively. This demonstrates the significant potential of a hip exoskeleton developed for walking assistance to profoundly benefit cycling. Additionally, customizing the assistance strategy proves beneficial in maximizing assistance. While we attribute the average motor power to be a major contributor to the reduced cycling effort, participant feedback suggests that user comfort and synchronization between the user and exoskeleton may have played integral roles. Further research should validate our initial findings by employing a larger participant pool in real-world conditions. Incorporating a more diverse set of parameters for the human-in-the-loop optimization could enhance individualized assistance strategies.