Effect of Substrates' Compliance on the Jumping Mechanism of Locusta migratoria

Putting a new spin on insect jumping performance using 3D modeling and computer simulations of spotted lanternfly nymphs

How animals jump and land on diverse surfaces is ecologically important and relevant to bioinspired robotics. Here, we describe the jumping biomechanics of the planthopper Lycorma delicatula (spotted lanternfly), an invasive insect in the USA that jumps frequently for dispersal, locomotion and predator evasion. High-speed video was used to analyze jumping by spotted lanternfly nymphs from take-off to impact on compliant surfaces. These insects used rapid hindleg extensions to achieve high take-off speeds (2.7-3.4 m s-1) and accelerations (800-1000 m s-2), with mid-air trajectories consistent with ballistic motion without drag forces or steering. Despite rotating rapidly (5-45 Hz) about time-varying axes of rotation, they landed successfully in 58.9% of trials. They also attained the most successful impact orientation significantly more often than predicted by chance, consistent with their using attitude control. Notably, these insects were able to land successfully when impacting surfaces at all angles, pointing to the importance of collisional recovery behaviors. To further understand their rotational dynamics, we created realistic 3D rendered models of spotted lanternflies and used them to compute their mechanical properties during jumping. Computer simulations based on these models and drag torques estimated from fits to tracked data successfully predicted several features of the measured rotational kinematics. This analysis showed that the rotational inertia of spotted lanternfly nymphs is predominantly due to their legs, enabling them to use posture changes as well as drag torque to control their angular velocity, and hence their orientation, thereby facilitating predominately successful landings when jumping.

Adapting small jumping robots to compliant environments

Jumping animals launch themselves from surfaces that vary widely in compliance from grasses and shrubs to tree branches. However, studies of robotic jumpers have been largely limited to those jumping from rigid substrates. In this paper, we leverage recent work describing how latches in jumping systems can mediate the transition from stored potential energy to kinetic energy. By including a description of the latch in our system model of both the jumper and compliant substrate, we can describe conditions in which a jumper can either lose energy to the substrate or recover energy from the substrate resulting in an improved jump performance. Using our mathematical model, we illustrate how the latch plays a role in the ability of a system to adapt its jump performance to a wide range of substrates that vary in their compliance. Our modelling results are validated using a 4 g jumper with a range of latch designs jumping from substrates with varying mass and compliance. Finally, we demonstrate the jumper recovering energy from a tree branch during take-off, extending these mechanistic findings to robots interacting with a more natural environment.

Controlling a One-Legged Robot to Clear Obstacles by Combining the SLIP Model with Air Trajectory Planning

Legged animals can adapt to complex terrains because they can step or jump over obstacles. Their application of foot force is determined according to the estimation of the height of an obstacle; then, the trajectory of the legs is controlled to clear the obstacle. In this paper, we designed a three-DoF one-legged robot. A spring-loaded inverted pendulum model was employed to control the jumping. Herein, the jumping height was mapped to the foot force by mimicking the jumping control mechanisms of animals. The foot trajectory in the air was planned using the Bézier curve. Finally, the experiments of the one-legged robot jumping over multiple obstacles of different heights were implemented in the PyBullet simulation environment. The simulation results demonstrate the effectiveness of the method proposed in this paper.

Flexibility Effects of a Flapping Mechanism Inspired by Insect Musculoskeletal System on Flight Performance

Flying animals such as insects display great flight performances with high stability and maneuverability even under unpredictable disturbances in natural and man-made environments. Unlike man-made mechanical systems like a drone, insects can achieve various flapping motions through their flexible musculoskeletal systems. However, it remains poorly understood whether flexibility affects flight performances or not. Here, we conducted an experimental study on the effects of the flexibility associated with the flapping mechanisms on aerodynamic performance with a flexible flapping mechanism (FFM) inspired by the flexible musculoskeletal system of insects. Based on wing kinematic and force measurements, we found an appropriate combination of the flexible components could improve the aerodynamic efficiency by increasing the wingbeat amplitude. Results of the wind tunnel experiments suggested that, through some passive adjustment of the wing kinematics in concert with the flexible mechanism, the disturbance-induced effects could be suppressed. Therefore, the flight stability under the disturbances is improved. While the FFM with the most rigid spring was least efficient in the static experiments, the model was most robust against the wind within the range of the study. Our results, particularly regarding the trade-off between the efficiency and the robustness, point out the importance of the passive response of the flapping mechanisms, which may provide a functional biomimetic design for the flapping micro air vehicles (MAVs) capable of achieving high efficiency and stability.

Influences of Different Drop Height Training on Lower Extremity Kinematics and Stiffness during Repetitive Drop Jump

Drop jump (DJ) is often used as a plyometric exercise to improve jumping performance. Training from improper drop heights and for improper durations lead to unfavorable biomechanical changes in the lower extremities when landing, which result in reduced training effects and even lower extremity injuries. Purpose. To study the effects of repeated DJ training at drop heights of 30 cm, 40 cm, and 50 cm (drop jump height (DJH) 30, DJH40, and DJH50) on lower extremity kinematics and kinetics. The 1st, 50th, 100th, 150th, and 200th DJs (DJ1, DJs50, DJs100, DJs150, and DJs200) were recorded by using a BTS motion capture system and force platform. The MATLAB software was used to compare the kinematic and stiffness data of DJ1, DJs50, DJs100, DJs150, and DJs200 with one-way ANOVA repeated measure. If there were significant differences, the LSD method was used for post hoc comparisons. Methods. Twenty healthy male Division III athlete volunteers were selected as subjects, and 200 drop jumps (DJs200) were performed from DJH30, DJH40, and DJH50. Results. The jumping height (JH), contact time (CT), and GRF increased with drop height, and the stiffness of the legs and ankle at DJH30 was higher than that at DJH40 and DJH50 (p < 0.05). Conclusion. Within DJs200, training at DJH50 yield the high impact easily leads to lower extremity injury; training at DJH30 can increase the stiffnesses of the legs and ankle joints, thus effectively utilizing the SSC benefits to store and release elastic energy, reducing the risk of lower extremity musculoskeletal injury. Therefore, coaches can choose different drop heights and training quantities for each person to better prevent lower extremity injury.

Jumping Locomotion Strategies: From Animals to Bioinspired Robots

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.

Beetle-robot hybrid interaction: sex, lateralization and mating experience modulate behavioural responses to robotic cues in the larger grain borer Prostephanus truncatus (Horn)

Ethorobotics, a new fascinating field of biorobotics, proposes the use of robotic replicas as an advanced method for investigating animal behaviour. This novel research approach can also encourage the development of advanced bioinspired robots. In the present study, we investigated the pushing behaviour, a particular display occurring in several beetle species, such as the larger grain borer, Prostephanus truncatus, during both male-female and male-male contexts. We developed a robotic apparatus actuating female and male-mimicking dummies to study if sex, mating experience and asymmetries of robotic cues can modulate the escalation of pushing behaviour. Results showed that the time needed by P. truncatus to react to female-smelling biomimetic dummies was chiefly affected by their mating experience and the dummy odour. This was likely due to reduce waste of costly sperm in mated males during the subsequent sexual interactions. The pushing behaviour was performed longer and with a higher number of acts when virgin females were approached from their right side. More and longer pushing acts were noted when virgin males were approached from their left side. Dedicated neural circuits would likely act in opposite direction in females and males producing population-level lateralized sensory-motor displays, which may be evolved to promote male approaches from the left side of females, thus improving short-distance sex recognition. Overall, this study provides new insights on the behavioural ecology of stored-product beetles, as well as on self-organization and decentralized decision making that can be exploited to develop bioinspired algorithms for task optimization, involving real-world scenarios.