Animal joint motion is a combination of rotation and translational motion, which brings high stability, high energy utilization, and other advantages. At present, the hinge joint is widely used in the legged robot. The simple motion characteristic of the hinge joint rotating around the fixed axis limits the improvement of the robot’s motion performance. In this paper, by imitating the knee joint of a kangaroo, we propose a new bionic geared five-bar knee joint mechanism to improve the energy utilization rate of the legged robot and reduce the required driving power. Firstly, based on image processing technology, the trajectory curve of the instantaneous center of rotation (ICR) of the kangaroo knee joint was quickly obtained. Then, the bionic knee joint was designed by the single-degree-of-freedom geared five-bar mechanism and the parameters for each part of the mechanism were optimized. Finally, based on the inverted pendulum model and the Newton–Euler recursive method, the dynamics model of the single leg of the robot in the landing stage was established, and the influence of the designed bionic knee joint and hinge joint on the robot’s motion performance was compared and analyzed. The proposed bionic geared five-bar knee joint mechanism can more closely track the given trajectory of the total center of mass motion, has abundant motion characteristics, and can effectively reduce the power demand and energy consumption of the robot knee actuators under the high-speed running and jumping gait.

This paper presents a novel design for a bionic knee exoskeleton equipped with a variable stiffness actuator based on rope-driven artificial muscles. To meet the varying stiffness requirements of the knee joint across different gait modes, the actuator dynamically switches between multiple rope bundle configurations, thereby enabling effective stiffness modulation. A mathematical model of the knee exoskeleton is developed, and the mechanical properties of the selected flexible aramid fiber ropes under tensile loading are analyzed through both theoretical and experimental approaches. Furthermore, a control framework for the exoskeleton system is proposed. Wearable experiments are conducted to evaluate the effectiveness of the variable stiffness actuation in improving compliance and comfort across various gait patterns. Electromyography (EMG) results further demonstrate that the exoskeleton provides a compensatory effect on the rectus femoris muscle.

Due to the high power-to-weight ratio and robustness, hydraulic cylinders are widely used in the actuation area of the legged robot systems. Most of these applications are focused on the motion stability, gait planning, and impedance control. However, the energy efficiency of the legged robotic system is also a very important point to be considered. Hopping locomotion requires a fast extension of the tibia leg at the end of the take-off phase, which causes a continuous increment of the cylinder velocity under the normally direct attachment geometry (DAG) of the cylinder. This leads to a high flow requirement, large pressure drop, and low energy efficiency. Therefore, we propose a four-bar mechanism attachment geometry (FMAG) to improve the energy efficiency by refining the relationship between the joint angle and cylinder displacement trend. The kinematic and dynamic models of the bionic one-legged robot are built to calculate the hopping process during the take-off phase. Based on the established dynamic models, the design parameters in both the DAG and FMAG are optimized to maximize the hopping height, respectively. The hopping experiments are conducted to verify the effectiveness of the new attachment geometry. The experimental results show that the robot hopping energy at the end of the take-off phase increases 14.8% under the FMAG.

This study analyzed the spatial distribution characteristics of the foot-end trajectory of a robotic leg mechanism during different gait phases. Based on this analysis, a task space partition-based dimensional parameter optimization method was proposed. To further evaluate the spatial distribution of the high-performance transmission regions after optimization, a box-counting dimension and lacunarity were introduced as supplementary characterization indices. First, according to the functional requirements of different gait phases, the task space of the mechanism is partitioned into stance, mid-swing, and swing-transition regions. A unified kinematic model and singularity criterion are then established for the planar five-bar mechanism, and mechanism performance indices for different task regions are constructed based on the Jacobian matrix to characterize the force and velocity transmission capabilities of the mechanism, as well as its singularity margin. A genetic algorithm is used to perform dimensional synthesis optimization of the mechanism parameters. Furthermore, a task space transmission performance field is introduced, and the area ratio, box-counting dimension, and lacunarity of regions with high performance are used to characterize the spatial structure of high-performance transmission regions before and after optimization. Finally, a series of theoretical calculations and physical experiments are conducted to verify that the differential characteristics of the mechanism have a significant influence on both its static and dynamic performance. The experimental results show that the optimized mechanism achieves lower normalized objective values in all task regions and outperforms the reference mechanism in load capacity, static power consumption, positioning accuracy, and trajectory consistency. The maximum static load capacity reaches 1.29 times that of the reference mechanism, while the static power consumption is reduced to approximately one half of that of the reference mechanism.