System-of-Systems Considerations in the Notional Development of a Metropolitan Aerial Transportation System

There are substantial future challenges related to sustaining and improving efficient, cost-effective, and environmentally friendly transportation options for urban regions. Over the past several decades there has been a worldwide trend towards increasing urbanization of society. Accompanying this urbanization are increasing surface transportation infrastructure costs and, despite public infrastructure investments, increasing surface transportation "gridlock." In addition to this global urbanization trend, there has been a substantial increase in concern regarding energy sustainability, fossil fuel emissions, and the potential implications of global climate change. A recently completed study investigated the feasibility of an aviation solution for future urban transportation (refs. 1, 2). Such an aerial transportation system could ideally address some of the above noted concerns related to urbanization, transportation gridlock, and fossil fuel emissions (ref. 3). A metro/regional aerial transportation system could also provide enhanced transportation flexibility to accommodate extraordinary events such as surface (rail/road) transportation network disruptions and emergency/disaster relief responses

Composite prototyping and vision based hierarchical control of a quad tilt-wing UAV

As the attention to unmanned systems is increasing, unmanned aerial vehicles (UAVs) are becoming more popular based on the rapid advances in technology and growth in operational experience. The main motivation in this vast research field is to diminish the human driven tasks by employing UAVs in critical civilian and military tasks such as traffic monitoring, disasters, surveillance, reconnaissance and border security. Researchers have been developing featured UAVs with intelligent navigation and control systems on more efficient designs aiming to increase the functionality, flight time and maneuverability. This thesis focuses on the composite prototyping and vision based hierarchical control of a quad tilt-wing aerial vehicle (SUAVI: Sabanci University Unmanned Aerial VehIcle). With the tilt-wing mechanism, SUAVI is one of the most challenging UAV concepts by combining advantages of vertical take-off and landing (VTOL) and horizontal flight. Various composite materials are tested for their mechanical properties and the most suitable one is used for prototyping of the aerial vehicle. A hierarchical control structure which consists of high-level and low-level controllers is developed. A vision based high-level controller generates attitude references for the low-level controllers. A Kalman filter fuses data from low-cost inertial sensors to obtain reliable orientation information. Low-level controllers are typically gravity compensated PID controllers. An image based visual servoing (IBVS) algorithm for VTOL, hovering and trajectory tracking is successfully implemented in simulations. Real flight tests demonstrate satisfactory performance of the developed control algorithms

HILS based Waypoint Simulation for Fixed Wing Unmanned Aerial Vehicle (UAV)

Hardware in loop simulation HILS-based waypoint simulation for fixed wing unmanned aerial vehicles is proposed in this paper. It uses an open-source arducopter as a flight controller, mission planner, and X-plane simulator. Waypoint simulation is carried out in the flight controller and executed in an X-plane simulator through a mission planner. A fixed wing unmanned aerial vehicle with an inverted T tail configuration has been chosen to study and validate waypoint flight control algorithms. The data transmission between mission planner and flight controller is done by serial protocol, whereas data exchange between X-plane and mission planner is done by User Datagram Protocol (UDP). APM mission planner is used as a machine interface to exchange data between the flight controller and the user. User inputs and flight gain parameters, both inner loop and outer loop, can be modified with the help of a mission planner. In addition to that, the mission planner provides a visual output representation of flight data and navigation algorithm

Aerial-Ground collaborative sensing: Third-Person view for teleoperation

Rapid deployment and operation are key requirements in time critical application, such as Search and Rescue (SaR). Efficiently teleoperated ground robots can support first-responders in such situations. However, first-person view teleoperation is sub-optimal in difficult terrains, while a third-person perspective can drastically increase teleoperation performance. Here, we propose a Micro Aerial Vehicle (MAV)-based system that can autonomously provide third-person perspective to ground robots. While our approach is based on local visual servoing, it further leverages the global localization of several ground robots to seamlessly transfer between these ground robots in GPS-denied environments. Therewith one MAV can support multiple ground robots on a demand basis. Furthermore, our system enables different visual detection regimes, and enhanced operability, and return-home functionality. We evaluate our system in real-world SaR scenarios.Comment: Accepted for publication in 2018 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR

The Phoenix Drone: An Open-Source Dual-Rotor Tail-Sitter Platform for Research and Education

In this paper, we introduce the Phoenix drone: the first completely open-source tail-sitter micro aerial vehicle (MAV) platform. The vehicle has a highly versatile, dual-rotor design and is engineered to be low-cost and easily extensible/modifiable. Our open-source release includes all of the design documents, software resources, and simulation tools needed to build and fly a high-performance tail-sitter for research and educational purposes. The drone has been developed for precision flight with a high degree of control authority. Our design methodology included extensive testing and characterization of the aerodynamic properties of the vehicle. The platform incorporates many off-the-shelf components and 3D-printed parts, in order to keep the cost down. Nonetheless, the paper includes results from flight trials which demonstrate that the vehicle is capable of very stable hovering and accurate trajectory tracking. Our hope is that the open-source Phoenix reference design will be useful to both researchers and educators. In particular, the details in this paper and the available open-source materials should enable learners to gain an understanding of aerodynamics, flight control, state estimation, software design, and simulation, while experimenting with a unique aerial robot.Comment: In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'19), Montreal, Canada, May 20-24, 201

AggieAir: Towards Low-cost Cooperative Multispectral Remote Sensing Using Small Unmanned Aircraft Systems

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Detecting and avoiding frontal obstacles from monocular camera for micro unmanned aerial vehicles

In literature, several approaches are trying to make the UAVs fly autonomously i.e., by extracting perspective cues such as straight lines. However, it is only available in well-defined human made environments, in addition to many other cues which require enough texture information. Our main target is to detect and avoid frontal obstacles from a monocular camera using a quad rotor Ar.Drone 2 by exploiting optical flow as a motion parallax, the drone is permitted to fly at a speed of 1 m/s and an altitude ranging from 1 to 4 meters above the ground level. In general, detecting and avoiding frontal obstacle is a quite challenging problem because optical flow has some limitation which should be taken into account i.e. lighting conditions and aperture problem

A novel distributed architecture for UAV indoor navigation

Abstract In the last decade, different indoor flight navigation systems for small Unmanned Aerial Vehicles (UAVs) have been investigated, with a special focus on different configurations and on sensor technologies. The main idea of this paper is to propose a distributed Guidance Navigation and Control (GNC) system architecture, based on Robotic Operation System (ROS) for light weight UAV autonomous indoor flight. The proposed framework is shown to be more robust and flexible than common configurations. A flight controller and companion computer running ROS for control and navigation are also included in the section. Both hardware and software diagrams are given to show the complete architecture. Further works will be based on the experimental validation of the proposed configuration by indoor flight tests