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Insecta

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Next generation insect taxonomic classification by comparing different deep learning algorithms.

PloS one
Insect taxonomy lies at the heart of many aspects of ecology, and identification tasks are challenging due to the enormous inter- and intraspecies variation of insects. Conventional methods used to study insect taxonomy are often tedious, time-consum...

Accommodating unobservability to control flight attitude with optic flow.

Nature
Attitude control is an essential flight capability. Whereas flying robots commonly rely on accelerometers for estimating attitude, flying insects lack an unambiguous sense of gravity. Despite the established role of several sense organs in attitude s...

Based on the multi-scale information sharing network of fine-grained attention for agricultural pest detection.

PloS one
It is of great significance to identify the pest species accurately and control it effectively to reduce the loss of agricultural products. The research results of this project will provide theoretical basis for preventing and controlling the spread ...

Shape classification technology of pollinated tomato flowers for robotic implementation.

Scientific reports
Three pollination methods are commonly used in the greenhouse cultivation of tomato. These are pollination using insects, artificial pollination (by manually vibrating flowers), and plant growth regulators. Insect pollination is the preferred natural...

Yolo-Pest: An Insect Pest Object Detection Algorithm via CAC3 Module.

Sensors (Basel, Switzerland)
Insect pests have always been one of the main hazards affecting crop yield and quality in traditional agriculture. An accurate and timely pest detection algorithm is essential for effective pest control; however, the existing approach suffers from a ...

Agricultural Robot-Centered Recognition of Early-Developmental Pest Stage Based on Deep Learning: A Case Study on Fall Armyworm ().

Sensors (Basel, Switzerland)
Accurately detecting early developmental stages of insect pests (larvae) from off-the-shelf stereo camera sensor data using deep learning holds several benefits for farmers, from simple robot configuration to early neutralization of this less agile b...

A virtuous cycle between invertebrate and robotics research: perspective on a decade of Living Machines research.

Bioinspiration & biomimetics
Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across domains while possessing smaller nervous systems than vertebrates. Three areas are particularly relevan...

A Review of Successes and Impeding Challenges of IoT-Based Insect Pest Detection Systems for Estimating Agroecosystem Health and Productivity of Cotton.

Sensors (Basel, Switzerland)
Using artificial intelligence (AI) and the IoT (Internet of Things) is a primary focus of applied engineering research to improve agricultural efficiency. This review paper summarizes the engagement of artificial intelligence models and IoT technique...

Dynamic turning and running of a hexapod robot using a separated and laterally arranged two-leg model.

Bioinspiration & biomimetics
We report on the development of separated and laterally arranged two-leg (SLTL) models with/without differentiated leg properties and their use as the dynamic running and turning templates for a hexapod robot. The laterally arranged two-leg morpholog...

Air-to-land transitions: from wingless animals and plant seeds to shuttlecocks and bio-inspired robots.

Bioinspiration & biomimetics
Recent observations of wingless animals, including jumping nematodes, springtails, insects, and wingless vertebrates like geckos, snakes, and salamanders, have shown that their adaptations and body morphing are essential for rapid self-righting and c...