Development of an Autonomous Blimp

The purpose of this project was to design and fabricate an autonomous dirigible-based platform that could be used to enable development of navigational controllers and provide multi-mission capability through modularity. The platform was designed to carry and interface with a variety of mission specific hardware through a standard interface. A customized hardware platform was designed including a propulsion system and integrated sensor suite. Multiple ground level tests were undertaken to determine sensor performance and the capabilities of the navigational programs

Development of an aerial robot for inspection and surveillance

Mestrado em Engenharia MecânicaOs veículos aéreos não tripulados são cada vez mais procurados para desempenhar diversas tarefas do quotidiano. Estes sistemas são, no entanto, caros e necessitam de equipas grandes para serem operados. O controlo de veículos aéreos autónomos num ambiente parcialmente conhecido é uma tarefa complexa. Os sistemas actuais são baseados em sensores e sistemas de controlo relativamente dispendiosos, e são frequentemente pesados, necessitando de uma grande quantidade de energia. O principal objectivo deste projecto é desenvolver um sistema aéreo não tripulado, fácil de operar, para inspecção e monitorização. Integrados neste sistema encontram-se a plataforma do robô aéreo, o sistema de controlo e a estação de controlo remoto. A plataforma desenvolvida é baseada em veículos mais leves que o ar. Pretende-se que esta plataforma seja capaz de navegar por espaços confinados e também em ambientes fechados. A esta plataforma foram incorporados sensores e sistemas de controlo leves e de baixo consumo de energia. Para a estação de supervisão foi desenvolvido um programa que permite o controlo do robô e supervisão dos objectivos da missão. A interface gráfica permite de uma forma intuitiva efectuar o controlo do robô. Os testes iniciais permitiram demonstrar as capacidades dos sistemas desenvolvidos para atingir os objectivos propostos. ABSTRACT: Unmanned aerial vehicles are being increasingly sought to perform every days tasks. But these systems are still costly and require a large crew of mission controllers and pilots to adequately manoeuvre the UAV. Managing and control an autonomous air vehicle in a partially known and uncontrolled environment is a complex problem. Current UAVs are based on costly sensors and control systems. These control systems are also usually heavy and demand large amounts of power. This thesis aims to develop an easy to operate unmanned aerial system for surveillance and monitoring missions. As part of this system will be developed an aerial platform, the embedded control system, the ground station with a graphical interface. The platform designed is based on a small lighter-than-air vehicle. To successfully complete the mission objectives the UAV must be capable of navigate through constrained areas and endow indoor flights. The UAV is equipped with low power consumption sensors and processors. For the ground station will be developed an application to control and monitor the UAV status. The graphical user interface application provide an easy to use interface to control and monitor the mission objectives. The initial tests allowed to validate the feasibility of the systems developed to achieve the proposed goals

Wide-Area Surveillance System using a UAV Helicopter Interceptor and Sensor Placement Planning Techniques

This project proposes and describes the implementation of a wide-area surveillance system comprised of a sensor/interceptor placement planning and an interceptor unmanned aerial vehicle (UAV) helicopter. Given the 2-D layout of an area, the planning system optimally places perimeter cameras based on maximum coverage and minimal cost. Part of this planning system includes the MATLAB implementation of Erdem and Sclaroff’s Radial Sweep algorithm for visibility polygon generation. Additionally, 2-D camera modeling is proposed for both fixed and PTZ cases. Finally, the interceptor is also placed to minimize shortest-path flight time to any point on the perimeter during a detection event. Secondly, a basic flight control system for the UAV helicopter is designed and implemented. The flight control system’s primary goal is to hover the helicopter in place when a human operator holds an automatic-flight switch. This system represents the first step in a complete waypoint-navigation flight control system. The flight control system is based on an inertial measurement unit (IMU) and a proportional-integral-derivative (PID) controller. This system is implemented using a general-purpose personal computer (GPPC) running Windows XP and other commercial off-the-shelf (COTS) hardware. This setup differs from other helicopter control systems which typically use custom embedded solutions or micro-controllers. Experiments demonstrate the sensor placement planning achieving \u3e90% coverage at optimized-cost for several typical areas given multiple camera types and parameters. Furthermore, the helicopter flight control system experiments achieve hovering success over short flight periods. However, the final conclusion is that the COTS IMU is insufficient for high-speed, high-frequency applications such as a helicopter control system

Vision-based automatic landing of a rotary UAV

A hybrid-like (continuous and discrete-event) approach to controlling a small multi-rotor unmanned aerial system (UAS) while landing on a moving platform is described. The landing scheme is based on positioning visual markers on a landing platform in a detectable pattern. After the onboard camera detects the object pattern, the inner control algorithm sends visual-based servo-commands to align the multi-rotor with the targets. This method is less computationally complex as it uses color-based object detection applied to a geometric pattern instead of feature tracking algorithms, and has the advantage of not requiring the distance to the objects to be calculated. The continuous approach accounts for the UAV and the platform rolling/pitching/yawing, which is essential for a real-time landing on a moving target such as a ship. A discrete-event supervisor working in parallel with the inner controller is designed to assist the automatic landing of a multi-rotor UAV on a moving target. This supervisory control strategy allows the pilot and crew to make time-critical decisions when exceptions, such as losing targets from the field of view, occur. The developed supervisor improves the low-level vision-based auto-landing system and high-level human-machine interface. The proposed hybrid-like approach was tested in simulation using a quadcopter model in Virtual Robotics Experimentation Platform (V-REP) working in parallel with Robot Operating System (ROS). Finally, this method was validated in a series of real-time experiments with indoor and outdoor quadcopters landing on both static and moving platforms. The developed prototype system has demonstrated the capability of landing within 25 cm of the desired point of touchdown. This auto-landing system is small (100 x 100 mm), light-weight (100 g), and consumes little power (under 2 W)

Optic Flow Based Autopilots: Speed Control and Obstacle Avoidance

International audienceThe explicit control schemes presented here explain how insects may navigate on the sole basis of optic flow (OF) cues without requiring any distance or speed measurements: how they take off and land, follow the terrain, avoid the lateral walls in a corridor and control their forward speed automatically. The optic flow regulator, a feedback system controlling either the lift, the forward thrust or the lateral thrust, is described. Three OF regulators account for various insect flight patterns observed over the ground and over still water, under calm and windy conditions and in straight and tapered corridors. These control schemes were simulated experimentally and/or implemented onboard two types of aerial robots, a micro helicopter (MH) and a hovercraft (HO), which behaved much like insects when placed in similar environments. These robots were equipped with opto-electronic OF sensors inspired by our electrophysiological findings on houseflies' motion sensitive visual neurons. The simple, parsimonious control schemes described here require no conventional avionic devices such as range finders, groundspeed sensors or GPS receivers. They are consistent with the the neural repertoire of flying insects and meet the low avionic payload requirements of autonomous micro aerial and space vehicles

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Touch the Wind: Simultaneous Airflow, Drag and Interaction Sensing on a Multirotor

Disturbance estimation for Micro Aerial Vehicles (MAVs) is crucial for robustness and safety. In this paper, we use novel, bio-inspired airflow sensors to measure the airflow acting on a MAV, and we fuse this information in an Unscented Kalman Filter (UKF) to simultaneously estimate the three-dimensional wind vector, the drag force, and other interaction forces (e.g. due to collisions, interaction with a human) acting on the robot. To this end, we present and compare a fully model-based and a deep learning-based strategy. The model-based approach considers the MAV and airflow sensor dynamics and its interaction with the wind, while the deep learning-based strategy uses a Long Short-Term Memory (LSTM) neural network to obtain an estimate of the relative airflow, which is then fused in the proposed filter. We validate our methods in hardware experiments, showing that we can accurately estimate relative airflow of up to 4 m/s, and we can differentiate drag and interaction force.Comment: The first two authors contributed equall

A Survey of path following control strategies for UAVs focused on quadrotors

The trajectory control problem, defined as making a vehicle follow a pre-established path in space, can be solved by means of trajectory tracking or path following. In the trajectory tracking problem a timed reference position is tracked. The path following approach removes any time dependence of the problem, resulting in many advantages on the control performance and design. An exhaustive review of path following algorithms applied to quadrotor vehicles has been carried out, the most relevant are studied in this paper. Then, four of these algorithms have been implemented and compared in a quadrotor simulation platform: Backstepping and Feedback Linearisation control-oriented algorithms and NLGL and Carrot-Chasing geometric algorithms.Peer ReviewedPostprint (author's final draft