Putting a new spin on insect jumping performance using 3D modeling and computer simulations of spotted lanternfly nymphs.
Chengpei LiAaron J XuEric BeeryS Tonia HsiehSuzanne Amador KanePublished in: The Journal of experimental biology (2023)
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 US 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 midair 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.
Keyphrases
- high speed
- climate change
- biofilm formation
- atomic force microscopy
- deep learning
- escherichia coli
- high resolution
- big data
- pseudomonas aeruginosa
- electronic health record
- mass spectrometry
- staphylococcus aureus
- blood flow
- artificial intelligence
- single molecule
- density functional theory
- quantum dots
- data analysis
- loop mediated isothermal amplification