Jumping is a locomotion strategy widely evolved in both invertebrates and vertebrates. In addition to terrestrial animals, several aquatic animals are also able to jump in their specific environments. In this paper, the state of the art of jumping robots has been systematically analyzed, based on their biological model, including invertebrates (e.g., jumping spiders, locusts, fleas, crickets, cockroaches, froghoppers and leafhoppers), vertebrates (e.g., frogs, galagoes, kangaroos, humans, dogs), as well as aquatic animals (e.g., both invertebrates and vertebrates, such as crabs, water-striders, and dolphins). The strategies adopted by animals and robots to control the jump (e.g., take-off angle, take-off direction, take-off velocity and take-off stability), aerial righting, land buffering, and resetting are concluded and compared. Based on this, the developmental trends of bioinspired jumping robots are predicted.

Locusts keep their bodies moving in a straight line during the takeoff and maintain the body stable during the whole jumping with small pitching motions, ensuring both kinematic and dynamic stability to reach their intended destinations. Inspired by locusts’ jumping performance, the Stephenson II six-bar jumping mechanism is adopted to mimic the kinematic stability of locusts’ takeoff and a dynamic model is developed to analyze the impacts of the torsional spring location, the spring stiffness, and the location of the equivalent body bar centroid on the jumping performance. Furthermore, a revised eight-bar jumping mechanism is proposed to solve the difficulty in realizing dynamic stability using the six-bar mechanism, as the moments of momentum of each component around the overall centroid are positive and contribute together to the counterclockwise rotation of the jumping. The dynamic modeling shows that the mass of the equivalent tarsus bar plays an important role in realizing the dynamic stability for the eight-bar jumping mechanism. Finally, two kinds of jumping robots are designed, fabricated and tested with jumping performance recorded by high-speed cameras, which validates the impacts of the mass of the equivalent tarsus bar on the jumping stability in the eight-bar jumping mechanism.

Beetle antennae search algorithm (BAS) is based on the searching behavior of longhorn beetles. This newly proposed metaheuristic algorithm is used in the path and function synthesis of multi-bar mechanism. The optimization results are compared with that of other metaheuristic algorithms like genetic algorithm (GA), particle swarm optimization (PSO) and differential evolution (DE) et al. While BAS uses only one group of initial parameters to search the best result, the convergence and efficiency are tested with eight case studies results. Newly added parameter q increases the possibility to find better results during iterations and deals with a higher number of independent parameters efficiently. Revised BAS exhibits good performance both in path synthesis of four-bar mechanism with or without prescribed timing, while optimized parameters increases from 6 to 34, and extends to path and function combined synthesis of Stephenson III six-bar double dwell mechanism with 14 parameters.

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.