AIMC Topic: Insecta

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Analysis and actuation design of a novel at-scale 3-DOF biomimetic flapping-wing mechanism inspired by flying insects.

Bioinspiration & biomimetics
Insects' flight is imbued with endless mysteries, offering valuable inspiration to the flapping-wing robots. Particularly, the multi-mode wingbeat motion such as flapping, sweeping and twisting in coordination presents advantages in promoting unstead...

Trap colour strongly affects the ability of deep learning models to recognize insect species in images of sticky traps.

Pest management science
BACKGROUND: The use of computer vision and deep learning models to automatically classify insect species on sticky traps has proven to be a cost- and time-efficient approach to pest monitoring. As different species are attracted to different colours,...

Visually guided swarm motion coordination via insect-inspired small target motion reactions.

Bioinspiration & biomimetics
Despite progress developing experimentally-consistent models of insect in-flight sensing and feedback for individual agents, a lack of systematic understanding of the multi-agent and group performance of the resulting bio-inspired sensing and feedbac...

Bio-inspired compensatory strategies for damage to flapping robotic propulsors.

Journal of the Royal Society, Interface
Natural swimmers and flyers can fully recover from catastrophic propulsor damage by altering stroke mechanics: some fish can lose even 76% of their propulsive surface without loss of thrust. We consider applying these principles to enable robotic fla...

Comparison of water and terrestrial jumping in natural and robotic insects.

Annals of the New York Academy of Sciences
Jumping requires high actuation power for achieving high speed in a short time. Especially, organisms and robots at the insect scale jump in order to overcome size limits on the speed of locomotion. As small jumpers suffer from intrinsically small po...

Detection and recognition of the invasive species, Hylurgus ligniperda, in traps, based on a cascaded convolution neural network.

Pest management science
BACKGROUND: Hylurgus ligniperda, an invasive species originating from Eurasia, is now a major forestry quarantine pest worldwide. In recent years, it has caused significant damage in China. While traps have been effective in monitoring and controllin...

Design and control of jumping microrobots with torque reversal latches.

Bioinspiration & biomimetics
Jumping microrobots and insects power their impressive leaps through systems of springs and latches. Using springs and latches, rather than motors or muscles, as actuators to power jumps imposes new challenges on controlling the performance of the ju...

Automated identification of aquatic insects: A case study using deep learning and computer vision techniques.

The Science of the total environment
Deep learning techniques have recently found application in biodiversity research. Mayflies (Ephemeroptera), stoneflies (Plecoptera) and caddisflies (Trichoptera), often abbreviated as EPT, are frequently used for freshwater biomonitoring due to thei...

InsectSound1000 An insect sound dataset for deep learning based acoustic insect recognition.

Scientific data
InsectSound1000 is a dataset comprising more than 169000 labelled sound samples of 12 insects. The insect sound level spans from very loud (Bombus terrestris) to inaudible to human ears (Aphidoletes aphidimyza). The samples were extracted from more t...

Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Automated sensors have potential to standardize and expand the monitoring of insects across the globe. As one of the most scalable and fastest developing sensor technologies, we describe a framework for automated, image-based monitoring of nocturnal ...