Fast, Accurate Thin-Structure Obstacle Detection for Autonomous Mobile Robots

Safety is paramount for mobile robotic platforms such as self-driving cars and unmanned aerial vehicles. This work is devoted to a task that is indispensable for safety yet was largely overlooked in the past -- detecting obstacles that are of very thin structures, such as wires, cables and tree branches. This is a challenging problem, as thin objects can be problematic for active sensors such as lidar and sonar and even for stereo cameras. In this work, we propose to use video sequences for thin obstacle detection. We represent obstacles with edges in the video frames, and reconstruct them in 3D using efficient edge-based visual odometry techniques. We provide both a monocular camera solution and a stereo camera solution. The former incorporates Inertial Measurement Unit (IMU) data to solve scale ambiguity, while the latter enjoys a novel, purely vision-based solution. Experiments demonstrated that the proposed methods are fast and able to detect thin obstacles robustly and accurately under various conditions.Comment: Appeared at IEEE CVPR 2017 Workshop on Embedded Visio

Сучасні методи моніторингу високовольтних ліній електропередач

Transmission lines require timely inspection and monitoring to prevent emergency situations during operation. System emergency situations as blackout are very undesirable, so they need their previous detection and prevention. Accordingly, this can be avoided by detailed monitoring the functioning of all elements of the power system. The directions of remote control for researching the operational state of electric power facilities through the use of special equipment, in particular aerial vehicles, have gained sufficient development. Possibilities of practical means of remote monitoring of power transmission lines are also considered. Due to their relatively inexpensive use and ease of operation, distant controlled aerial vehicles are an effective approach for surveying high-voltage power lines. A number of advantages of using distant controlled aerial vehicles are the extended functionality of monitoring quality provided by modern equipment. Functional analysis of modern on-board equipment indicates the possibility of detecting research objects on a real-time scale, due to the use of telemetry, satellite and combined television and thermal imaging systems, with the possibility of detailed observe. The most perspective is the use of combined heat-television systems, which allow improving the technical characteristics of the surveillance system significantly. This method provides monitoring of heat losses, detection of overheated elements of transmission lines and assessment of the performance of elements. Such technology ensures more safer and timely detection of malfunctions, threats to operation and carrying out work on their elimination. In addition, the fields of application of distant controlled aerial vehicles as surveys for the design of energy systems are increasing.Лінії електропередач потребують своєчасного обстеження та моніторингу для запобігання аварійні ситуації при експлуатації. Системні аварійні ситуації є дуже небажаними, тому потребують передчасного їх виявлення і запобігання. Відповідно, цього можна уникнути, якщо проводити ретельний моніторинг роботи всіх елементів енергосистеми. Достатнього розвитку набули напрямки дистанційного контролю для дослідження експлуатаційного стану електроенергетичних об’єктів за рахунок використання спеціального обладнання, зокрема літальних апаратів. Також розглянуто можливості з практичних засобів дистанційного моніторингу ліній електропередачі. Завдяки порівняно недорогому використанню і простоті експлуатації, дистанційно керовані літальні апарати є ефективним інструментом для обстеження високовольтних ліній електропередач. Низка переваг використання дистанційно керованого літального апарата полягає у розширених функціональних можливостях з якості моніторингу, що забезпечується сучасним обладнанням. Функціональний аналіз сучасного бортового обладнання вказує на можливості виявлення об’єктів дослідження в реальному масштабі часу, за рахунок застосування телеметричних, супутникових та комбінованих телевізійних та тепловізійних систем, з можливістю детального обстеження. Найбільш перспективним є застосування комбінованих тепло-телевізійних систем що дозволяє істотно підвищити технічні характеристики системи спостереження. Такий підхід забезпечує моніторинг теплових втрат, виявлення перегрітих елементів ліній електропередачі та оцінку працездатності елементів. Така технологія забезпечує більш безпечне та своєчасне виявлення несправностей, загроз експлуатації та проведення робіт з їх усунення. Крім того, збільшуються галузі застосування дистанційно керованих літальних апаратів у якості обстежень задля проектування енергосистем

Aerial Drone Control Networks

The goal of this project is to create an easy-to-expand Unmanned Aerial Vehicle (UAV) platform capable of conducting coordinated wide-area reconnaissance. Our system uses a combination of off-the-shelf components and open-source software to enable custom mission creation. Each drone packages and sends image, position, and orientation data over a WiFi connection to a centralized ground station computer for processing. Potential applications for this system range from search-and-rescue to surveying and inspection

ESTABLISHING NEW FOUNDATIONS FOR THE USE OF REMOTELY-PILOTED AIRCRAFT SYSTEMS FOR CIVILIAN APPLICATIONS

Abstract. Skyopener is a project funded by the EU through the European GNSS Agency (GSA) in the framework of the Horizon 2020 program. Skyopener's goal is contributing to the roadmap for the integration of civil Remotely Piloted Aircraft Systems (RPAS) into nonsegregated airspace, by providing and testing enabling technologies, in particular with reference to European initiative U-Space, aimed at establishing regulations and infrastructure for integration of unmanned aviation into shared airspace. The main outcomes of the project include: implementing and testing a reliable and secure redundant air-ground communication link, based on satellite and 3G/4G networks; integrating the mission management system and ground station with a UTM (Unmanned aerial system Traffic Management) client, and experimenting UTM services being deployed by one of the partners; demonstrating technical and economic feasibility of long- range missions beyond visual line of sight (BVLOS) by executing corridor mapping on a high-voltage powerline, and airport area surveys (e-TOD: electronic-Terrain Obstacle Database).</p

Drones and Digital Photogrammetry: From Classifications to Continuums for Monitoring River Habitat and Hydromorphology

Recently, we have gained the opportunity to obtain very high-resolution imagery and topographic data of rivers using drones and novel digital photogrammetric processing techniques. The high-resolution outputs from this method are unprecedented, and provide the opportunity to move beyond river habitat classification systems, and work directly with spatially explicit continuums of data. Traditionally, classification systems have formed the backbone of physical river habitat monitoring for their ease of use, rapidity, cost efficiency, and direct comparability. Yet such classifications fail to characterize the detailed heterogeneity of habitat, especially those features which are small or marginal. Drones and digital photogrammetry now provide an alternative approach for monitoring river habitat and hydromorphology, which we review here using two case studies. First, we demonstrate the classification of river habitat using drone imagery acquired in 2012 of a 120 m section of the San Pedro River in Chile, which was at the technological limits of what could be achieved at that time. Second, we review how continuums of data can be acquired, using drone imagery acquired in 2016 from the River Teme in Herefordshire, England. We investigate the precision and accuracy of these data continuums, highlight key current challenges, and review current best practices of data collection, processing, and management. We encourage further quantitative testing and field applications. If current difficulties can be overcome, these continuums of geomorphic and hydraulic information hold great potential for providing new opportunities for understanding river systems to the benefit of both river science and management

Drones and digital photogrammetry: from classifications to continuums for monitoring river habitat and hydromorphology

Recently, we have gained the opportunity to obtain very high-resolution imagery and topographic data of rivers using drones and novel digital photogrammetric processing techniques. The high-resolution outputs from this method are unprecedented, and provide the opportunity to move beyond river habitat classification systems, and work directly with spatially explicit continuums of data. Traditionally, classification systems have formed the backbone of physical river habitat monitoring for their ease of use, rapidity, cost efficiency, and direct comparability. Yet such classifications fail to characterize the detailed heterogeneity of habitat, especially those features which are small or marginal. Drones and digital photogrammetry now provide an alternative approach for monitoring river habitat and hydromorphology, which we review here using two case studies. First, we demonstrate the classification of river habitat using drone imagery acquired in 2012 of a 120 m section of the San Pedro River in Chile, which was at the technological limits of what could be achieved at that time. Second, we review how continuums of data can be acquired, using drone imagery acquired in 2016 from the River Teme in Herefordshire, England. We investigate the precision and accuracy of these data continuums, highlight key current challenges, and review current best practices of data collection, processing, and management. We encourage further quantitative testing and field applications. If current difficulties can be overcome, these continuums of geomorphic and hydraulic information hold great potential for providing new opportunities for understanding river systems to the benefit of both river science and management

Automatic Crack Segmentation for UAV-assisted Bridge Inspection

Bridges are a critical piece of infrastructure in the network of road and rail transport system. Many of the bridges in Norway (in Europe) are at the end of their lifespan, therefore regular inspection and maintenance are critical to ensure the safety of their operations. However, the traditional inspection procedures and resources required are so time consuming and costly that there exists a significant maintenance backlog. The central thrust of this paper is to demonstrate the significant benefits of adapting a Unmanned Aerial Vehicle (UAV)-assisted inspection to reduce the time and costs of bridge inspection and established the research needs associated with the processing of the (big) data produced by such autonomous technologies. In this regard, a methodology is proposed for analysing the bridge damage that comprises three key stages, (i) data collection and model training, where one performs experiments and trials to perfect drone flights for inspection using case study bridges to inform and provide necessary (big) data for the second key stage, (ii) 3D construction, where one built 3D models that offer a permanent record of element geometry for each bridge asset, which could be used for navigation and control purposes, (iii) damage identification and analysis, where deep learning-based data analytics and modelling are applied for processing and analysing UAV image data and to perform bridge damage performance assessment. The proposed methodology is exemplified via UAV-assisted inspection of Skodsberg bridge, a 140 m prestressed concrete bridge, in the Viken county in eastern Norway.publishedVersio

The GRIFFIN perception dataset: Bridging the gap between flapping-wing flight and robotic perception

The development of automatic perception systems and techniques for bio-inspired flapping-wing robots is severely hampered by the high technical complexity of these platforms and the installation of onboard sensors and electronics. Besides, flapping-wing robot perception suffers from high vibration levels and abrupt movements during flight, which cause motion blur and strong changes in lighting conditions. This letter presents a perception dataset for bird-scale flapping-wing robots as a tool to help alleviate the aforementioned problems. The presented data include measurements from onboard sensors widely used in aerial robotics and suitable to deal with the perception challenges of flapping-wing robots, such as an event camera, a conventional camera, and two Inertial Measurement Units (IMUs), as well as ground truth measurements from a laser tracker or a motion capture system. A total of 21 datasets of different types of flights were collected in three different scenarios (one indoor and two outdoor). To the best of the authors' knowledge this is the first dataset for flapping-wing robot perceptionConsejo Europeo de Investigación 788247ARM-EXTEND DPI2017-8979-