Enhancing the explosive power output of the knee joints is critical for improving the agility and obstacle-crossing capabilities of humanoid robots. However, a mismatch between the knee-to-center-of-mass (CoM) transmission ratio and jumping demands, coupled with motor performance degradation at high speeds, restricts the duration of high-power output and limits jump performance. To address these problems, this paper introduces a novel knee joint design paradigm employing a dynamically decreasing reduction ratio for explosive output during jump. Analysis of motor output characteristics and knee kinematics during jumping inspired a coupling strategy in which the reduction ratio gradually decreases as the joint extends. A high initial ratio rapidly increases torque at jump initiation, while its gradual reduction minimizes motor speed increments and power losses, thereby maintaining sustained high-power output. A compact and efficient linear actuator-driven guide-rod mechanism realizes this coupling strategy, supported by parameter optimization guided by explosive jump control strategies. Experimental validation demonstrated a 63 cm vertical jump on a single-joint platform (a theoretical improvement of 28.1\% over the optimal fixed-ratio joints). Integrated into a humanoid robot, the proposed design enabled a 1.1 m long jump, a 0.5 m vertical jump, and a 0.5 m box jump.

Background: Lower limb exoskeletons can enhance quality of life, but widespread adoption is limited by the lack of frameworks to assess their biomechanical and human-robot interaction effects, which are essential for developing adaptive and personalized control strategies. Understanding impacts on kinematics, muscle activity, and HRI dynamics is key to achieve improved usability of wearable robots. Objectives: We propose a systematic methodology evaluate an ankle exoskeleton's effects on human movement during walking and load-carrying (10 kg front pack), focusing on joint kinematics, muscle activity, and HRI torque signals. Materials and Methods: Using Xsens MVN (inertial motion capture), Delsys EMG, and a unilateral exoskeleton, three experiments were conducted: (1) isolated dorsiflexion/plantarflexion; (2) gait analysis (two subjects, passive/active modes); and (3) load-carrying under assistance. Results and Conclusions: The first experiment confirmed that the HRI sensor captured both voluntary and involuntary torques, providing directional torque insights. The second experiment showed that the device slightly restricted ankle range of motion (RoM) but supported normal gait patterns across all assistance modes. The exoskeleton reduced muscle activity, particularly in active mode. HRI torque varied according to gait phases and highlighted reduced synchronization, suggesting a need for improved support. The third experiment revealed that load-carrying increased GM and TA muscle activity, but the device partially mitigated user effort by reducing muscle activity compared to unassisted walking. HRI increased during load-carrying, providing insights into user-device dynamics. These results demonstrate the importance of tailoring exoskeleton evaluation methods to specific devices and users, while offering a framework for future studies on exoskeleton biomechanics and HRI.

Most birds can navigate seamlessly between aerial and terrestrial environments. Whereas the forelimbs evolved into wings primarily for flight, the hindlimbs serve diverse functions such as walking, hopping, and leaping, and jumping take-off for transitions into flight. These capabilities have inspired engineers to aim for similar multi-modality in aerial robots, expanding their range of applications across diverse environments. However, challenges remain in reproducing multi-modal locomotion, across gaits with distinct kinematics and propulsive characteristics, such as walking and jumping, while preserving lightweight mass for flight. This tradeoff between mechanical complexity and versatility limits most existing aerial robots to only one additional locomotor mode. Here, we overcome the complexity-versatility tradeoff with RAVEN (Robotic Avian-inspired Vehicle for multiple ENvironments), which uses its bird-inspired multi-functional legs to jump rapidly into flight, walk on ground and hop over obstacles and gaps similar to the multi-modal locomotion of birds. We show that jumping for take-off contributes substantially to initial flight take-off speed and, remarkably, that it is more energy-efficient than solely propeller-based take-off. Our analysis suggests an important tradeoff in mass distribution between legs and body among birds adapted for different locomotor strategies, with greater investment in leg mass among terrestrial birds with multi-modal gait demands. Multi-functional robot legs expand opportunities to deploy traditional fixed-wing aircraft in complex terrains through autonomous take-offs and multi-modal gaits.

Many studies have been conducted on Series Elastic Actuators (SEA) for robot joints because they are effective in terms of flexibility, safety, and energy efficiency. The ability of SEA to robustly handle unexpected disturbances has raised expectations for practical applications in environments where robots interact with humans. On the other hand, the development and commercialization of small robots for indoor entertainment applications is also actively underway, and it is thought that by using SEA in these robots, dynamic movements such as jumping and running can be realized. In this work, we developed a small and lightweight SEA using coil springs as elastic elements. By devising a method for fixing the coil spring, it is possible to absorb shock and perform highly accurate force measurement in both rotational directions with a simple structure. In addition, to verify the effectiveness of the developed SEA, we created a small single-legged robot with SEA implemented in the three joints of the hip, knee, and ankle, and we conducted a drop test. By adjusting the initial posture and control gain of each joint, we confirmed that flexible landing and continuous hopping are possible with simple PD position control. The measurement results showed that SEA is effective in terms of shock absorption and energy reuse. This work was performed for research purposes only.

Despite decades of study, many unknowns exist about the mechanisms governing human locomotion. Current models and motor control theories can only partially capture the phenomenon. This may be a major cause of the reduced efficacy of lower limb rehabilitation therapies. Recently, it has been proposed that human locomotion can be planned in the task-space by taking advantage of the gravitational pull acting on the Centre of Mass (CoM) by modelling the attractor dynamics. The model proposed represents the CoM transversal trajectory as a harmonic oscillator propagating on the attractor manifold. However, the vertical trajectory of the CoM, controlled through ankle strategies, has not been accurately captured yet. Research Questions: Is it possible to improve the model accuracy by introducing a mathematical model of the ankle strategies by coordinating the heel-strike and toe-off strategies with the CoM movement? Our solution consists of closed-form equations that plan human-like trajectories for the CoM, the foot swing, and the ankle strategies. We have tested our model by extracting the biomechanics data and postural during locomotion from the motion capture trajectories of 12 healthy subjects at 3 self-selected speeds to generate a virtual subject using our model. Our virtual subject has been based on the average of the collected data. The model output shows our virtual subject has walking trajectories that have their features consistent with our motion capture data. Additionally, it emerged from the data analysis that our model regulates the stance phase of the foot as humans do. The model proves that locomotion can be modelled as an attractor dynamics, proving the existence of a nonlinear map that our nervous system learns. It can support a deeper investigation of locomotion motor control, potentially improving locomotion rehabilitation and assistive technologies.

Producing an artificial general intelligence (AGI) has been an elusive goal in artificial intelligence (AI) research for some time. An AGI would have the capability, like a human, to be exposed to a new problem domain, learn about it and then use reasoning processes to make decisions. While AI techniques have been used across a wide variety of problem domains, an AGI would require an AI that could reason beyond its programming and training. This paper presents a small step towards producing an AGI. It describes a mechanism for an AI to learn about and develop reasoning pathways to make decisions in an a priori unknown domain. It combines a classical AI technique, the expert system, with a its modern adaptation - the gradient descent trained expert system (GDTES) - and utilizes generative artificial intelligence (GAI) to create a network and training data set for this system. These can be created from available sources or may draw upon knowledge incorporated in a GAI's own pre-trained model. The learning process in GDTES is used to optimize the AI's decision-making. While this approach does not meet the standards that many have defined for an AGI, it provides a somewhat similar capability, albeit one which requires a learning process before use.

For lower limb amputees, an active ankle joint prosthesis can provide basic mobility functions. This study focuses on an ankle joint prosthesis system based on the principle of electric-hydraulic actuation. By analyzing the characteristics of human gait cycles and the mechanics of ankle joint movement, a lightweight and integrated ankle joint prosthesis is designed, considering the requirements for normal ankle joint kinematics and dynamics. The components of the prosthesis are optimized through simulation and iterative improvements, while ensuring tight integration within minimal space. The design and simulation verification of the integrated lightweight prosthesis components are achieved. This research addresses the contradiction between the high output capability and the constraints on volume and weight in prosthetic devices.

Humans possess a remarkable ability to react to sudden and unpredictable perturbations through immediate mechanical responses, which harness the visco-elastic properties of muscles to perform auto-corrective movements to maintain balance. In this paper, we propose a novel design of a robotic leg inspired by this mechanism. We develop multi-material fibre jammed tendons, and demonstrate their use as passive compliant mechanisms to achieve variable joint stiffness and improve stability. Through numerical simulations and extensive experimentation, we demonstrate the ability for our system to achieve a wide range of potentially beneficial compliance regimes. We show the role and contribution of each tendon quantitatively by evaluating their individual force contribution in resisting rotational perturbations. We also perform walking experiments with programmed bioinspired gaits that varying the stiffness of the tendons throughout the gait cycle, demonstrating a stable and consistent behaviour. We show the potential of such systems when integrated into legged robots, where compliance and shock absorption can be provided entirely through the morphological properties of the leg.

Jet engines can have up to 25,000 individual parts, making regular maintenance a tedious task that can take over a month per engine. Many components are located deep inside the engine and cannot be inspected without taking the machine apart, adding time and costs to maintenance. This problem is not only confined to jet engines, either; many complicated, expensive machines like construction equipment, generators, and scientific instruments require large investments of time and money to inspect and maintain. Researchers at Harvard University's Wyss Institute for Biologically Inspired Engineering and John A. Paulson School of Engineering and Applied Sciences (SEAS) have created a micro-robot whose electroadhesive foot pads, origami ankle joints, and specially engineered walking gait allow it to climb on vertical and upside-down conductive surfaces, like the inside walls of a commercial jet engine. The work is reported in Science Robotics.

Last year, US Army-funded plans for a flexible exosuit designed to help soldiers carry heavy loads were revealed. Now, a new study has shown exactly how much energy the soft exosuit can save. Results published in a new paper show the suit reduces the effort it takes to walk by 23 per cent, by assisting the wearer's ankles and hips every time they take a step. The suit reduces the effort it takes to walk by 23 per cent, by assisting the wearer's ankles and hips every time they take a step. The Harvard suit comprises a waist belt, two thigh pieces and two calf straps, connected by cables to two motors mounted on a backpack.