Simulation of Flapping-wing Unmanned Aerial Vehicle using X-plane and Matlab/Simulink

This paper presents the simulation of flapping-wing unmanned aerial vehicle model using X-plane and Matlab/ Simulink. The flapping-wing ornithopter model (i.e. an aircraft that flies by flapping its wings) has been developed in plane maker software and executed in the X-plane environment. The key idea of flapping-wing mechanism in X-plane software is by varying its dihedral angle sinusoidally. This sinusoidally varying dihedral angle of wing creates upward and downward stroke moments inturn this creates a lift and a forward thrust for flying the flapping-wing model. Here pitch, roll, yaw and throttle (flapping rate) is fed as reference input through the user datagram protocol (UDP) port. The difference between the reference inputs, the simulated outputs are again fed back to simulator through UDP port and the gains are observed for the responses of flapping-wing unmanned aerial vehicle in Matlab/Simulink environment. Here various gains are used to monitor the optimized flying of flapping-wing model.Defence Science Journal, Vol. 64, No. 4, July 2014, pp.327-331, DOI:http://dx.doi.org/10.14429/dsj.64.493

An Intelligent Autopilot System that learns piloting skills from human pilots by imitation

An Intelligent Autopilot System (IAS) that can learn piloting skills by observing and imitating expert human pilots is proposed. IAS is a potential solution to the current problem of Automatic Flight Control Systems of being unable to handle flight uncertainties, and the need to construct control models manually. A robust Learning by Imitation approach is proposed which uses human pilots to demonstrate the task to be learned in a flight simulator while training datasets are captured from these demonstrations. The datasets are then used by Artificial Neural Networks to generate control models automatically. The control models imitate the skills of the human pilot when performing piloting tasks including handling flight uncertainties such as severe weather conditions. Experiments show that IAS performs learned take-off, climb, and slow ascent tasks with high accuracy even after being presented with limited examples, as measured by Mean Absolute Error and Mean Absolute Deviation. The results demonstrate that the IAS is capable of imitating low-level sub-cognitive skills such as rapid and continuous stabilization attempts in stormy weather conditions, and high-level strategic skills such as the sequence of sub-tasks necessary to pilot an aircraft starting from the stationary position on the runway, and ending with a steady cruise

Enabling technologies for precise aerial manufacturing with unmanned aerial vehicles

The construction industry is currently experiencing a revolution with automation techniques such as additive manufacturing and robot-enabled construction. Additive Manufacturing (AM) is a key technology that can o er productivity improvement in the construction industry by means of o -site prefabrication and on-site construction with automated systems. The key bene t is that building elements can be fabricated with less materials and higher design freedom compared to traditional manual methods. O -site prefabrication with AM has been investigated for some time already, but it has limitations in terms of logistical issues of components transportation and due to its lack of design exibility on-site. On-site construction with automated systems, such as static gantry systems and mobile ground robots performing AM tasks, can o er additional bene ts over o -site prefabrication, but it needs further research before it will become practical and economical. Ground-based automated construction systems also have the limitation that they cannot extend the construction envelope beyond their physical size. The solution of using aerial robots to liberate the process from the constrained construction envelope has been suggested, albeit with technological challenges including precision of operation, uncertainty in environmental interaction and energy e ciency. This thesis investigates methods of precise manufacturing with aerial robots. In particular, this work focuses on stabilisation mechanisms and origami-based structural elements that allow aerial robots to operate in challenging environments. An integrated aerial self-aligning delta manipulator has been utilised to increase the positioning accuracy of the aerial robots, and a Material Extrusion (ME) process has been developed for Aerial Additive Manufacturing (AAM). A 28-layer tower has been additively manufactured by aerial robots to demonstrate the feasibility of AAM. Rotorigami and a bioinspired landing mechanism demonstrate their abilities to overcome uncertainty in environmental interaction with impact protection capabilities and improved robustness for UAV. Design principles using tensile anchoring methods have been explored, enabling low-power operation and explores possibility of low-power aerial stabilisation. The results demonstrate that precise aerial manufacturing needs to consider not only just the robotic aspects, such as ight control algorithms and mechatronics, but also material behaviour and environmental interaction as factors for its success.Open Acces

Experimental Characterization of the Structural Dynamics and Aero-Structural Sensitivity of a Hawkmoth Wing Toward the Development of Design Rules for Flapping Wing Micro Air Vehicles

A case is made for why the structures discipline must take on a more central role in the research and design of flapping-wing micro-air-vehicles, especially if research trends continue toward bio-inspired, insect-sized flexible wing designs. In making the case, the eigenstructure of the wing emerges as a key structural metric for consideration. But with virtually no structural dynamic data available for actual insect wings, both engineered and computational wing models that have been inspired by biological analogs have no structural truth models to which they can be anchored. An experimental framework is therefore developed herein for performing system identification testing on the wings of insects. This framework is then utilized to characterize the structural dynamics of the forewing of a large sample of hawkmoth (Manduca Sexta) for future design and research consideration. The research also weighs-in on a decade-long debate as to the relative contributions that the inertial and fluid dynamic forces acting on a flapping insect wing have on its deformation (expression) during flight. Ultimately the findings proves that both affect wing expression significantly, casting serious doubt on the longstanding and most frequently cited research that indicates fluid dynamic forces have minimal or negligible effect

Modern computing: Vision and challenges

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress

Development of Faster SMA Actuators

Large cycle time, resulted from slow cooling, is the core hindrance to the wide spread applications of shape memory alloys (SMAs) as actuators. This chapter discusses a novel cooling technique to decrease the cycle time of SMAs. Under this technique, the SMA actuator of 0.15 mm diameter was run through a grease-filled Polytetrafluoroethylene (PTFE) tube of 0.5 mm outside diameter. Later, same tests were repeated with oil filled PTFE tube. The test results conducted in ambient air were used as standard for comparison. The actuation current in ambient air was set at 210, 310 and 410 mA. While testing with heat sink, i.e. grease and oil, the SMA was heated with 210, 310, 410, 500, 615 and 720 mA currents for 1 and 2 seconds, whereas the SMA was heated for 1 second only with 810 mA current. It was found that the grease cooling reduced the cooling time up to 30% and oil cooling by 20%, as compared to the ambient air-cooling time. However, the grease-cooled actuators had shown less strain, and their response was non-linear at many instances. Heat loss to the sinks resulted to more power consumption than that in ambient air cooling for equivalent amount of strain

Modeling and Characterization of Bioinspired Hybrid Flapping/Gliding Flight for Flapping Wing Air Vehicles

Unmanned Aerial Vehicles (UAVs) are increasingly being used for applications that require longer, reliable flight duration and distances. The greatest limitation to achieving these desired flights is the current on board battery technology which, restricted by internal chemistry and external size, can only provide a finite amount of power over time. Efforts to increase the battery’s efficiency and energy storage tend to rely on cumbersome methods that add weight and/or complexity to the system. However natural flyers, though also limited by a finite amount of internal energy gained through food consumption, are able to extend their flights through techniques that either utilize their inherent aerodynamic advantages or advantageously employ atmospheric phenomena. Flapping-Wing UAVs (FWUAVs) are as limited by their onboard battery as any other type of UAV, but because of their bio-inspired functionality are uniquely suited to utilize natural flight extension methods. Therefore, this PhD presents an analysis of the exploration of bio-inspired, hybrid flapping/gliding, also known as intermittent gliding, techniques to improve the flight performance of a FWUAV. Robo Raven is the FWUAV that was chosen as the research platform for this work. It was developed by researchers at the University of Maryland to perform prolonged, untethered flights and exhibit a flight proficiency that combined the maneuverability of rotary-wing flight with the efficiency of fixed-wing flight. The technique to improve FWUAV flight time, presented in this work incorporates (1) the modeling of Robo Raven’s flapping/gliding potential through the development of a state-space representation directly linking Robo Raven’s onboard battery dynamics with its aerodynamic performance, (2) the use of the state-space model to characterize the effect of intermittent gliding techniques on flight performance through simulation, (3) the real-world characterization of the simulation and of intermittent gliding techniques through flight demonstrations, and (4) the development of a design space by which the effect of wing design on gliding performance might be explored and lead to the potential tailoring of wing design to desired flight performance. The expected outcome of this technique is scientific analysis of the extension of Robo Raven’s flight time without added complexity of weight of the battery system

Phase-advanced attitude sensing and control for fixed-wing micro aerial vehicles in turbulence

The scale of fixed-wing Micro Aerial Vehicles (MAVs) lend them to many unique applications. These applications often require low speed flights close to the ground, in the vicinity of large obstacles and in the wake of buildings. A particular challenge for MAVs is attitude control in the presence of high turbulence. Such flights pose a challenging operational environment for MAVs, and in particular, ensuring sufficient attitude control in the presence of significant turbulence. Low-level flight in the atmospheric boundary layer without sufficient attitude control is hazardous, mainly due to the high levels of turbulence intensity close to the ground. MAV accidents have occurred due to the lack of a reliable attitude control system in turbulent conditions as reported in the literature. Challenges associated with flight control of fixed-wing MAVs operating in complex environments are significantly different to any larger scale vehicle. The scale of MAVs makes them particularly sensitive to atmospheric disturbances thus limiting their operation. A review of the literature revealed that rolling inputs from turbulence were the most challenging whereby conventional inertial-based attitude control systems lack the responsiveness for roll control in high turbulence environments. The solution might lie with flying animals, which have adapted to flight within turbulence. The literature survey identified bio-inspired phase-advanced sensors as a promising sensory solution for complementing current reactive attitude sensors. The development of a novel bio-inspired phase-advanced sensor and associated control system, which can sense the flow disturbances before an attitude perturbation, is the focus of this research. The development of such a system required an in-depth understanding of the features of the disturbing phenomena; turbulence. Correlation studies were conducted between the oncoming turbulence and wing-surface pressure variations. It was found that the highest correlation exists between upstream flow pitch angle variation and the wing-surface pressure fluctuations. However, due to the insufficient time-forward advantage, surface pressure sensing was not used for attitude control. A second sensing approach was explored to cater for the control system’s time-lags. Multi-hole pressure probes were embedded in the wings of the MAV to sense flow pitch angle and magnitude variation upstream of the wing. The sensors provide an estimate of the disturbing turbulence. This approach caters for the time-lags of the system providing sufficient time to counteract the gust before it results in an inertial response. Statistical analysis was used to assess the disturbance rejection performance of the phase-advanced sensory system, which was benchmarked against a conventional inertial-based sensory system in a range of turbulence conditions. Unconstrained but controlled test flights were conducted inside the turbulence environment of two wind-tunnels, in addition to outdoor flight testing in the atmosphere. These three different turbulence conditions enabled testing of a wide range of turbulence spectra believed to be most detrimental to the MAV. A significant improvement in disturbance rejection performance was observed in relation to conventional inertial-based sensory systems. It can be concluded that sensory systems providing time-forward estimates of turbulence can complement conventional inertial-based sensors to improve the attitude stability performance

Advances in Bio-Inspired Robots

This book covers three major topics, specifically Biomimetic Robot Design, Mechanical System Design from Bio-Inspiration, and Bio-Inspired Analysis on A Mechanical System. The Biomimetic Robot Design part introduces research on flexible jumping robots, snake robots, and small flying robots, while the Mechanical System Design from Bio-Inspiration part introduces Bioinspired Divide-and-Conquer Design Methodology, Modular Cable-Driven Human-Like Robotic Arm andWall-Climbing Robot. Finally, in the Bio-Inspired Analysis on A Mechanical System part, research contents on the control strategy of Surgical Assistant Robot, modeling of Underwater Thruster, and optimization of Humanoid Robot are introduced