Vision Aided Automatic Landing System for Fixed Wing UAV

Abstract-In this paper, we present a multi-sensor system for automatic landing of fixed wing UAVs. The system is composed of a high precision aircraft controller and a vision module which is currently used for detection and tracking of runways. Designing the system we paid special attention to its robustness. The runway detection algorithm uses a maximum amount of information in images and works with high level geometrical models. It allows detecting a runway under different weather conditions even if only a small part is visible in the image. In order to increase landing reliability under sub-optimal wind conditions, an additional loop was introduced into the altitude controller. All control and image processing is performed onboard. The system has been successfully tested in flight experiments with two different fixed wing platforms at various weather conditions, in summer, fall and winter

Survey of computer vision algorithms and applications for unmanned aerial vehicles

This paper presents a complete review of computer vision algorithms and vision-based intelligent applications, that are developed in the field of the Unmanned Aerial Vehicles (UAVs) in the latest decade. During this time, the evolution of relevant technologies for UAVs; such as component miniaturization, the increase of computational capabilities, and the evolution of computer vision techniques have allowed an important advance in the development of UAVs technologies and applications. Particularly, computer vision technologies integrated in UAVs allow to develop cutting-edge technologies to cope with aerial perception difficulties; such as visual navigation algorithms, obstacle detection and avoidance and aerial decision-making. All these expert technologies have developed a wide spectrum of application for UAVs, beyond the classic military and defense purposes. Unmanned Aerial Vehicles and Computer Vision are common topics in expert systems, so thanks to the recent advances in perception technologies, modern intelligent applications are developed to enhance autonomous UAV positioning, or automatic algorithms to avoid aerial collisions, among others. Then, the presented survey is based on artificial perception applications that represent important advances in the latest years in the expert system field related to the Unmanned Aerial Vehicles. In this paper, the most significant advances in this field are presented, able to solve fundamental technical limitations; such as visual odometry, obstacle detection, mapping and localization, et cetera. Besides, they have been analyzed based on their capabilities and potential utility. Moreover, the applications and UAVs are divided and categorized according to different criteria.This research is supported by the Spanish Government through the CICYT projects (TRA2015-63708-R and TRA2013-48314-C3-1-R)

Unmanned Aerial Systems Research, Development, Education and Training at Embry-Riddle Aeronautical University

With technological breakthroughs in miniaturized aircraft-related components, including but not limited to communications, computer systems and sensors and, state-of-the-art unmanned aerial systems (UAS) have become a reality. This fast growing industry is anticipating and responding to a myriad of societal applications that will provide either new or more cost effective solutions that previous technologies could not, or will replace activities that involved humans in flight with associated risks. Embry-Riddle Aeronautical University has a long history of aviation related research and education, and is heavily engaged in UAS activities. This document provides a summary of these activities. The document is divided into two parts. The first part provides a brief summary of each of the various activities while the second part lists the faculty associated with those activities. Within the first part of this document we have separated the UAS activities into two broad areas: Engineering and Applications. Each of these broad areas is then further broken down into six sub-areas, which are listed in the Table of Contents. The second part lists the faculty, sorted by campus (Daytona Beach---D, Prescott---P and Worldwide--W) associated with the UAS activities. The UAS activities and the corresponding faculty are cross-referenced. We have chosen to provide very short summaries of the UAS activities rather than lengthy descriptions. Should more information be desired, please contact me directly or alternatively visit our research web pages (http://research.erau.edu) and contact the appropriate faculty member directly

A fly-by-wireless UAV platform based on a flexible and distributed system architecture

This paper reports and describes the diverse stages concerning the development of an unmanned aerial vehicle (UAV) named “Aeronave Inteligente com Visão Artificial”, better known by its acronym as AIVA. The design and development of the first aerial platform, the onboard ommunications, the instrumentation system, the bidirectional communications platform to/from ground station, the flight control system, the navigation strategies, as well as the vision systems to help navigation and to carry out the planned surveillance missions, are addressed in this paper. One of the main innovative issues of this platform is the distributed onboard wireless network, based on Bluetooth technology and on a multiprocessor architecture system. These features increase the platform flexibility. The goals already accomplished so far reveal interesting developments to be used successfully in commercial UAV platforms

Automatic Landing without GPS

Sagem Défense et Sécurité (now Safran Electronics & Defense), a French space and defense company of the SAFRAN group, is working on the next generation of Unmanned Aerial System (UAS). This UAS features a fully automatic Unmanned Aerial Vehicle (UAV) equipped with a state-of-the-art navigation system. This navigation system relies mainly on a high-accuracy Inertial Measurement Unit (IMU) coupled with a GPS receiver. But the GPS is known to be easy to jam, either naturally (solar flare for example) or intentionally. In the event of a loss of GPS signal, the navigation system is not able anymore to provide accurate position and speed information to the Flight Controller (FC). Deprived of reliable position and speed information the FC is not able to guide the UAV safely to the ground. So the goal of the project detailed in this report is to add to the existing UAS the ability to land safely in case of a GPS loss. At the core of the solution described in this report is a sensor fusion algorithm taking as input inertial, vision based, barometric, laser and azimuthal measurements. The filter is using all these measurements to establish reliable position and speed estimates. Even if very reliable systems enabling automatic landing without GPS exist today; they all require heavy and expensive ground equipment. This is why SAGEM decided to develop its own solution using more embedded sensors and less ground equipment. This is a first step toward a fully embedded automatic landing system nondependent on GPS availability, a very active field of research today. All the tests done during the thesis and presented in this report shows the efficiency and robustness of this solution

Towards an autonomous landing system in presence of uncertain obstacles in indoor environments

The landing task is fundamental to Micro air vehicles (MAVs) when attempting to land in an unpredictable environment (e.g., presence of static obstacles or moving obstacles). The MAV should immediately detect the environment through its sensors and decide its actions for landing. This paper addresses the problem of the autonomous landing approach of a commercial AR. Drone 2.0 in presence of uncertain obstacles in an indoor environment. A localization methodology to estimate the drone's pose based on the sensor fusion techniques which fuses IMU and Poxyz signals is proposed. In addition, a vision-based approach to detect and estimate the velocity, position of the moving obstacle in the drone's working environment is presented. To control the drone landing accurately, a cascade control based on an Accelerated Particle Swarm Optimization algorithm (APSO) is designed. The simulation and experimental results demonstrate that the obtained model is appropriate for the measured data

The AIVA fly-by-wireless UAV platform

The AIVA project concerns to an UAV aimed to perform aerial surveillance, forest fire detection and also to monitor high voltage cables for stress or failures. The global project involves the design and development of the required aerial platform, as well as the electronics, communications hardware and software, flight control, artificial vision and systems integration, in order to provide an autonomous takeoff, flight mission and landing manoeuvres. Relevant goals, regarding the design and development of the AIVA platform, initiated in September 2004, have already been achieved, and they will be described over next topics. [...

UAV Deployment Exercise for Mapping Purposes: Evaluation of Emergency Response Applications

Exploiting the decrease of costs related to UAV technology, the humanitarian community started piloting the use of similar systems in humanitarian crises several years ago in different application fields, i.e., disaster mapping and information gathering, community capacity building, logistics and even transportation of goods. Part of the author’s group, composed of researchers in the field of applied geomatics, has been piloting the use of UAVs since 2006, with a specific focus on disaster management application. In the framework of such activities, a UAV deployment exercise was jointly organized with the Regional Civil Protection authority, mainly aimed at assessing the operational procedures to deploy UAVs for mapping purposes and the usability of the acquired data in an emergency response context. In the paper the technical features of the UAV platforms will be described, comparing the main advantages/disadvantages of fixed-wing versus rotor platforms. The main phases of the adopted operational procedure will be discussed and assessed especially in terms of time required to carry out each step, highlighting potential bottlenecks and in view of the national regulation framework, which is rapidly evolving. Different methodologies for the processing of the acquired data will be described and discussed, evaluating the fitness for emergency response applications