AIMC Topic: Birds

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Metamorphic aerial robot capable of mid-air shape morphing for rapid perching.

Scientific reports
Aerial robots can perch onto structures at heights to reduce energy use or to remain firmly in place when interacting with their surroundings. Like how birds have wings to fly and legs to perch, these bio-inspired aerial robots use independent perchi...

An at-scale tailless flapping wing hummingbird robot: II. Flight control in hovering and trajectory tracking.

Bioinspiration & biomimetics
Flight control such as stable hovering and trajectory tracking of tailless flapping-wing micro aerial vehicles is a challenging task. Given the constraint on actuation capability, flight control authority is limited beyond sufficient lift generation....

Opportunistic soaring by birds suggests new opportunities for atmospheric energy harvesting by flying robots.

Journal of the Royal Society, Interface
The use of flying robots (drones) is increasing rapidly, but their utility is limited by high power demand, low specific energy storage and poor gust tolerance. By contrast, birds demonstrate long endurance, harvesting atmospheric energy in environme...

Bio-inspired flapping wing robots with foldable or deformable wings: a review.

Bioinspiration & biomimetics
Traditional flapping-wing robots (FWRs) obtain lift and thrust by relying on the passive deformation of their wings which cannot actively fold or deform. In contrast, flying creatures such as birds, bats, and insects can maneuver agilely through acti...

Fine-Grained Image Analysis With Deep Learning: A Survey.

IEEE transactions on pattern analysis and machine intelligence
Fine-grained image analysis (FGIA) is a longstanding and fundamental problem in computer vision and pattern recognition, and underpins a diverse set of real-world applications. The task of FGIA targets analyzing visual objects from subordinate catego...

A general deep learning model for bird detection in high-resolution airborne imagery.

Ecological applications : a publication of the Ecological Society of America
Advances in artificial intelligence for computer vision hold great promise for increasing the scales at which ecological systems can be studied. The distribution and behavior of individuals is central to ecology, and computer vision using deep neural...

Adaptive Modular Convolutional Neural Network for Image Recognition.

Sensors (Basel, Switzerland)
Image recognition has long been one of the research hotspots in computer vision tasks. The development of deep learning is rapid in recent years, and convolutional neural networks usually need to be designed with fixed resources. If sufficient resour...

Enhancement of Detection of Diabetic Retinopathy Using Harris Hawks Optimization with Deep Learning Model.

Computational intelligence and neuroscience
In today's world, diabetic retinopathy is a very severe health issue, which is affecting many humans of different age groups. Due to the high levels of blood sugar, the minuscule blood vessels in the retina may get damaged in no time and further may ...

Running birds reveal secrets for legged robot design.

Science robotics
Recapitulating avian locomotion opens the door for simple and economical control of legged robots without sensory feedback systems.

BirdBot achieves energy-efficient gait with minimal control using avian-inspired leg clutching.

Science robotics
Designers of legged robots are challenged with creating mechanisms that allow energy-efficient locomotion with robust and minimalistic control. Sources of high energy costs in legged robots include the rapid loading and high forces required to suppor...