A Study on the Control, Dynamics, and Hardware of Micro Aerial Biomimetic Flapping Wing Vehicles

Biological flight encapsulates 400 million years of evolutionary ingenuity and thus is the most efficient way to fly. If an engineering pursuit is not adhering to biomimetic inspiration, then it is probably not the most efficient design. An aircraft that is inspired by bird or other biological modes of flight is called an ornithopter and is the original design of the first airplanes. Flapping wings hold much engineering promise with the potential to produce lift and thrust simultaneously. In this research, modeling and simulation of a flapping wing vehicle is generated. The purpose of this research is to develop a control algorithm for a model describing flapping wing robotics. The modeling approach consists of initially considering the simplest possible model and subsequently building models of increasing complexity. This research finds that a proportional derivative feedback and feedforward controller applied to a nonlinear model is the most practical controller for a flapping system. Due to the complex aerodynamics of ornithopter flight, modeling and control are very difficult. Overall, this project aims to analyze and simulate different forms of biological flapping flight and robotic ornithopters, investigate different control methods, and also acquire understanding of the hardware of a flapping wing aerial vehicle

Living IoT: A Flying Wireless Platform on Live Insects

Sensor networks with devices capable of moving could enable applications ranging from precision irrigation to environmental sensing. Using mechanical drones to move sensors, however, severely limits operation time since flight time is limited by the energy density of current battery technology. We explore an alternative, biology-based solution: integrate sensing, computing and communication functionalities onto live flying insects to create a mobile IoT platform. Such an approach takes advantage of these tiny, highly efficient biological insects which are ubiquitous in many outdoor ecosystems, to essentially provide mobility for free. Doing so however requires addressing key technical challenges of power, size, weight and self-localization in order for the insects to perform location-dependent sensing operations as they carry our IoT payload through the environment. We develop and deploy our platform on bumblebees which includes backscatter communication, low-power self-localization hardware, sensors, and a power source. We show that our platform is capable of sensing, backscattering data at 1 kbps when the insects are back at the hive, and localizing itself up to distances of 80 m from the access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang, In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201

The implications of embodiment for behavior and cognition: animal and robotic case studies

In this paper, we will argue that if we want to understand the function of the brain (or the control in the case of robots), we must understand how the brain is embedded into the physical system, and how the organism interacts with the real world. While embodiment has often been used in its trivial meaning, i.e. 'intelligence requires a body', the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. A number of case studies are presented to illustrate the concept. These involve animals and robots and are concentrated around locomotion, grasping, and visual perception. A theoretical scheme that can be used to embed the diverse case studies will be presented. Finally, we will establish a link between the low-level sensory-motor processes and cognition. We will present an embodied view on categorization, and propose the concepts of 'body schema' and 'forward models' as a natural extension of the embodied approach toward first representations.Comment: Book chapter in W. Tschacher & C. Bergomi, ed., 'The Implications of Embodiment: Cognition and Communication', Exeter: Imprint Academic, pp. 31-5

Linear model identification of beetle-mimicking flapping wing micro-air vehicle in hovering flight

This paper presents a linear time invariant model identification for beetle mimicking flapping wing micro air vehicle (FWMAV) in hovering mode. The identification is facilitated by assuming the wings of the beetle rectangular in shape and the body is considered cylindrical. The main thrust is provided by flapping the wings of the FWMAV whereas the trailing-edges-change mechanism was kept off. The measurable aerodynamic forces and moment’s measured data are utilized in the states' reconstruction. The state reconstruction was carried out via the discrete time integration of linear and angular acceleration. Having reconstructed the states, the standard least mean square estimation (LMSE) based estimation approach is used to estimate the system’s stability and control derivatives. The results of the estimation are validated with the experimental data, and show the success of the estimation approach