Review of insect-inspired wing micro air vehicle

Insect wing flexibility improves the aerodynamic performance of small revolving wings

Insect wings are flexible, elastically deforming under loads experienced during flapping. The adaptive value of this flexibility was tested using a revolving wing set-up. We show that the wing flexibility of the beetle Batocera rufomaculata suppresses the reduction in lift coefficient that is expected to occur with a reduction of wing size compared to rigid propeller blades. Moreover, the scaling of wing flexibility with size is intra-specifically tuned through changes in wing-vein cross-section, resulting in smaller wings achieving proportionally larger chordwise deformations compared to larger wings, when loaded with aerodynamic forces. These elastic deformations control the separation of flow from the wing as a function of angle-of-attack, as evidenced by the turbulence activity in the flow field directly beneath the revolving wings. The study underlines the contribution of flexibility to control the flow over insect wings through passive wing deformations without the need for input or feedback from the nervous system.

Bio-inspired designs: leveraging biological brilliance in mechanical engineering-an overview

Nature's evolutionary mastery has perfected design over the years, yielding organisms superbly adapted to their surroundings. This research delves into the promising domain of bio-inspired designs, poised to revolutionize mechanical engineering. Leveraging insights drawn from prior conversations, we categorize innovations influenced by life on land, in water, and through the air, emphasizing their pivotal contributions to mechanical properties. Our comprehensive review reveals a wealth of bio-inspired designs that have already made substantial inroads in mechanical engineering. From avian-inspired lightweight yet robust materials to hydrodynamically optimized forms borrowed from marine creatures, these innovations hold immense potential for enhancing mechanical systems. In conclusion, this study underscores the transformative potential of bio-inspired designs, offering improved mechanical characteristics and the promise of sustainability and efficiency across a broad spectrum of applications. This research envisions a future where bio-inspired designs shape the mechanical landscape, fostering a more harmonious coexistence between human technology and the natural world.

Landing and take-off capabilities of bioinspired aerial vehicles: a review

Bioinspired flapping-wing micro aerial vehicles (FWMAVs) have emerged over the last two decades as a promising new type of robot. Their high thrust-to-weight ratio, versatility, safety, and maneuverability, especially at small scales, could make them more suitable than fixed-wing and multi-rotor vehicles for various applications, especially in cluttered, confined environments and in close proximity to humans, flora, and fauna. Unlike natural flyers, however, most FWMAVs currently have limited take-off and landing capabilities. Natural flyers are able to take off and land effortlessly from a wide variety of surfaces and in complex environments. Mimicking such capabilities on flapping-wing robots would considerably enhance their practical usage. This review presents an overview of take-off and landing techniques for FWMAVs, covering different approaches and mechanism designs, as well as dynamics and control aspects. The special case of perching is also included. As well as discussing solutions investigated for FWMAVs specifically, we also present solutions that have been developed for different types of robots but may be applicable to flapping-wing ones. Different approaches are compared and their suitability for different applications and types of robots is assessed. Moreover, research and technology gaps are identified, and promising future work directions are identified.

Detection of Hindwing Landmarks Using Transfer Learning and High-Resolution Networks

Hindwing venation is one of the most important morphological features for the functional and evolutionary analysis of beetles, as it is one of the key features used for the analysis of beetle flight performance and the design of beetle-like flapping wing micro aerial vehicles. However, manual landmark annotation for hindwing morphological analysis is a time-consuming process hindering the development of wing morphology research. In this paper, we present a novel approach for the detection of landmarks on the hindwings of leaf beetles (Coleoptera, Chrysomelidae) using a limited number of samples. The proposed method entails the transfer of a pre-existing model, trained on a large natural image dataset, to the specific domain of leaf beetle hindwings. This is achieved by using a deep high-resolution network as the backbone. The low-stage network parameters are frozen, while the high-stage parameters are re-trained to construct a leaf beetle hindwing landmark detection model. A leaf beetle hindwing landmark dataset was constructed, and the network was trained on varying numbers of randomly selected hindwing samples. The results demonstrate that the average detection normalized mean error for specific landmarks of leaf beetle hindwings (100 samples) remains below 0.02 and only reached 0.045 when using a mere three samples for training. Comparative analyses reveal that the proposed approach out-performs a prevalently used method (i.e., a deep residual network). This study showcases the practicability of employing natural images-specifically, those in ImageNet-for the purpose of pre-training leaf beetle hindwing landmark detection models in particular, providing a promising approach for insect wing venation digitization.