First lift-off and flight performance of a tailless flapping-wing aerial robot in high-altitude environments

Flapping flight of animals has captured the interest of researchers due to their impressive flight capabilities across diverse environments including mountains, oceans, forests, and urban areas. Despite the significant progress made in understanding flapping flight, high-altitude flight as showcased by many migrating animals remains underexplored. At high-altitudes, air density is low, and it is challenging to produce lift. Here we demonstrate a first lift-off of a flapping wing robot in a low-density environment through wing size and motion scaling. Force measurements showed that the lift remained high at 0.14 N despite a 66% reduction of air density from the sea-level condition. The flapping amplitude increased from 148 to 233 degrees, while the pitch amplitude remained nearly constant at 38.2 degrees. The combined effect is that the flapping-wing robot benefited from the angle of attack that is characteristic of flying animals. Our results suggest that it is not a simple increase in the flapping frequency, but a coordinated increase in the wing size and reduction in flapping frequency enables the flight in lower density condition. The key mechanism is to preserve the passive rotations due to wing deformation, confirmed by a bioinspired scaling relationship. Our results highlight the feasibility of flight under a low-density, high-altitude environment due to leveraging unsteady aerodynamic mechanisms unique to flapping wings. We anticipate our experimental demonstration to be a starting point for more sophisticated flapping wing models and robots for autonomous multi-altitude sensing. Furthermore, it is a preliminary step towards flapping wing flight in the ultra-low density Martian atmosphere.

Musculoskeletal wing-actuation model of hummingbirds predicts diverse effects of primary flight muscles in hovering flight

Hummingbirds have evolved to hover and manoeuvre with exceptional flight control. This is enabled by their musculoskeletal system that successfully exploits the agile motion of flapping wings. Here, we synthesize existing empirical and modelling data to generate novel hypotheses for principles of hummingbird wing actuation. These may help guide future experimental work and provide insights into the evolution and robotic emulation of hummingbird flight. We develop a functional model of the hummingbird musculoskeletal system, which predicts instantaneous, three-dimensional torque produced by primary (pectoralis and supracoracoideus) and combined secondary muscles. The model also predicts primary muscle contractile behaviour, including stress, strain, elasticity and work. Results suggest that the primary muscles (i.e. the flight 'engine') function as diverse effectors, as they do not simply power the stroke, but also actively deviate and pitch the wing with comparable actuation torque. The results also suggest that the secondary muscles produce controlled-tightening effects by acting against primary muscles in deviation and pitching. The diverse effects of the pectoralis are associated with the evolution of a comparatively enormous bicipital crest on the humerus.

A Natural Human-Drone Embodied Interface: Empirical Comparison With a Traditional Interface

Despite the importance of usability in human-machine interaction (HMI), most commonly used devices are not usable by all potential users. In particular, users with low or null technological experience, or with special needs, require carefully designed systems and easy-to-use interfaces supporting recognition over recall. To this purpose, Natural User Interfaces (NUIs) represent an effective strategy as the user's learning is facilitated by features of the interface that mimic the human “natural” sensorimotor embodied interactions with the environment. This paper compares the usability of a new NUI (based on an eye-tracker and hand gesture recognition) with a traditional interface (keyboard) for the distal control of a simulated drone flying in a virtual environment. The whole interface relies on “dAIsy”, a new software allowing the flexible use of different input devices and the control of different robotic platforms. The 59 users involved in the study were required to complete two tasks with each interface, while their performance was recorded: (a) exploration: detecting trees embedded in an urban environment; (b) accuracy: guiding the drone as accurately and fast as possible along a predefined track. Then they were administered questionnaires regarding the user's background, the perceived embodiment of the device, and the perceived quality of the virtual experience while either using the NUI or the traditional interface. The results appear controversial and call for further investigation: (a) contrary to our hypothesis, the specific NUI used led to lower performance than the traditional interface; (b) however, the NUI was evaluated as more natural and embodied. The final part of the paper discusses the possible causes underlying these results that suggest possible future improvements of the NUI.

Chaotic Image Encryption: State-of-the-Art, Ecosystem, and Future Roadmap

Recently, many researchers have been interested in the application of chaos in cryptography. Specifically, numerous research works have been focusing on chaotic image encryption. A comprehensive survey can highlight existing trends and shed light on less-studied topics in the area of chaotic image encryption. In addition to such a survey, this paper studies the main challenges in this field, establishes an ecosystem for chaotic image encryption, and develops a future roadmap for further research in this area.