Standard meteorological measurements on board of POLARSTERN during expedition ANT-IV (PS08, 4 cruises, south summer 1985/86) in the Atlantic and Weddell Sea, Antarctica

During the fourth Antarctic voyage ANT-IV of the research icebreaker POLARSTERN standard meteorological measurements have been performed. The measurements include 3-hourly synoptic observations as well as daily upper air soundings. The measurements started on September 6 1985 at Bremerhaven and were terminated at April 28 1986 in Punta Arenas. The 3-hourly synoptic observations are performed following the instructions of the FM 13 ships code defined by the World Meteorological Organization (WMO). The datasets include automatic measurements such as mean ship's speed, wind velocity, wind direction, air temperature, water temperature as well as visual observations such as total cloud amount, present weather, clouds, height and period of swell waves, ice classification. The visual observation are not performed during night time. For the upper air soundings VAISALA RS80 radiosondes, carried by helium-filled balloons (TOTEX 350 - 1500) were used. Data reception and evaluation were carried out by a MicroCora System (VAISALA). The upper air soundings include profile measurements of pressure, temperature, relative humidity and wind vector. Usually the soundings started at the heliport (10 m above sea level) and terminated between 15 and 37 km. The height of the measurements was calculated by applying the barometric formula. The wind vector was determined with the aid of the OMEGA navigation system.

Построение автоматической навигационной системы малогабаритного беспилотного летательного аппарата многократного применения = Development of automatic navigation management system for small unmanned aerial vehicle

Современный этап развития комплексов автоматического управления и навигации малогабаритными БЛА многократного применения предъявляет высокие требования к автономности, точности и миниатюрности данных систем. Противоречивость требований диктует использование функционального и алгоритмического объединения нескольких разнотипных источников навигационной информации в едином вычислительном процессе на основе методов оптимальной фильтрации. Получили широкое развитие бесплатформенные инерциальные навигационные системы (БИНС) на основе комплексирования данных микромеханических датчиков инерциальной информации и датчиков параметров движения в воздушном потоке с данными спутниковых навигационных систем (СНС). Однако в современных условиях такой подход не в полной мере реализует требования к помехозащищённости, автономности и точности получаемой навигационной информации. Одновременно с этим достигли значительного прогресса навигационные системы, использующие принципы корреляционно экстремальной навигации по оптическим ориентирам и цифровым картам местности. Предлагается схема построения автономной автоматической навигационной системы (АНС) для БЛА многоразового применения на основе объединения алгоритмов БИНС, спутниковой навигационной системы и оптической навигационной системы. The modern stage of automatic control and guidance systems development for small unmanned aerial vehicles (UAV) is determined by advanced requirements for autonomy, accuracy and size of the systems. The contradictory of the requirements dictates novel functional and algorithmic tight coupling of several different onboard sensors into one computational process, which is based on methods of optimal filtering. Nowadays, data fusion of micro-electro mechanical sensors of inertial measurement units, barometric pressure sensors, and signals of global navigation satellite systems (GNSS) receivers is widely used in numerous strap down inertial navigation systems (INS). However, the systems do not fully comply with such requirements as jamming immunity, fault tolerance, autonomy, and accuracy of navigation. At the same time, the significant progress has been recently demonstrated by the navigation systems, which use the correlation extremal principle applied for optical data flow and digital maps. This article proposes a new architecture of automatic navigation management system (ANMS) for small UAV, which combines algorithms of strap down INS, satellite navigation and optical navigation system.

The Information-analytical System for Diagnostics of Aircraft Navigation Units

The operation of technical processes requires increasingly advanced supervision and fault diagnostics to improve reliability and safety. This paper gives an introduction to the field of fault detection and diagnostics and has short methods classification. Growth of complexity and functional importance of inertial navigation systems leads to high losses at the equipment refusals. The paper is devoted to the INS diagnostics system development, allowing identifying the cause of malfunction. The practical realization of this system concerns a software package, performing a set of multidimensional information analysis. The project consists of three parts: subsystem for analyzing, subsystem for data collection and universal interface for open architecture realization. For a diagnostics improving in small analyzing samples new approaches based on pattern recognition algorithms voting and taking into account correlations between target and input parameters will be applied. The system now is at the development stage.

Investigation of MEMS inertial sensors and aircraft dynamic models in global positioning system integrity monitoring for approaches with vertical guidance

An Approach with Vertical Guidance (APV) is an instrument approach procedure which provides horizontal and vertical guidance to a pilot on approach to landing in reduced visibility conditions. APV approaches can greatly reduce the safety risk to general aviation by improving the pilot’s situational awareness. In particular the incidence of Controlled Flight Into Terrain (CFIT) which has occurred in a number of fatal air crashes in general aviation over the past decade in Australia, can be reduced. APV approaches can also improve general aviation operations. If implemented at Australian airports, APV approach procedures are expected to bring a cost saving of millions of dollars to the economy due to fewer missed approaches, diversions and an increased safety benefit. The provision of accurate horizontal and vertical guidance is achievable using the Global Positioning System (GPS). Because aviation is a safety of life application, an aviation-certified GPS receiver must have integrity monitoring or augmentation to ensure that its navigation solution can be trusted. However, the difficulty with the current GPS satellite constellation alone meeting APV integrity requirements, the susceptibility of GPS to jamming or interference and the potential shortcomings of proposed augmentation solutions for Australia such as the Ground-based Regional Augmentation System (GRAS) justifies the investigation of Aircraft Based Augmentation Systems (ABAS) as an alternative integrity solution for general aviation. ABAS augments GPS with other sensors at the aircraft to help it meet the integrity requirements. Typical ABAS designs assume high quality inertial sensors to provide an accurate reference trajectory for Kalman filters. Unfortunately high-quality inertial sensors are too expensive for general aviation. In contrast to these approaches the purpose of this research is to investigate fusing GPS with lower-cost Micro-Electro-Mechanical System (MEMS) Inertial Measurement Units (IMU) and a mathematical model of aircraft dynamics, referred to as an Aircraft Dynamic Model (ADM) in this thesis. Using a model of aircraft dynamics in navigation systems has been studied before in the available literature and shown to be useful particularly for aiding inertial coasting or attitude determination. In contrast to these applications, this thesis investigates its use in ABAS. This thesis presents an ABAS architecture concept which makes use of a MEMS IMU and ADM, named the General Aviation GPS Integrity System (GAGIS) for convenience. GAGIS includes a GPS, MEMS IMU, ADM, a bank of Extended Kalman Filters (EKF) and uses the Normalized Solution Separation (NSS) method for fault detection. The GPS, IMU and ADM information is fused together in a tightly-coupled configuration, with frequent GPS updates applied to correct the IMU and ADM. The use of both IMU and ADM allows for a number of different possible configurations. Three are investigated in this thesis; a GPS-IMU EKF, a GPS-ADM EKF and a GPS-IMU-ADM EKF. The integrity monitoring performance of the GPS-IMU EKF, GPS-ADM EKF and GPS-IMU-ADM EKF architectures are compared against each other and against a stand-alone GPS architecture in a series of computer simulation tests of an APV approach. Typical GPS, IMU, ADM and environmental errors are simulated. The simulation results show the GPS integrity monitoring performance achievable by augmenting GPS with an ADM and low-cost IMU for a general aviation aircraft on an APV approach. A contribution to research is made in determining whether a low-cost IMU or ADM can provide improved integrity monitoring performance over stand-alone GPS. It is found that a reduction of approximately 50% in protection levels is possible using the GPS-IMU EKF or GPS-ADM EKF as well as faster detection of a slowly growing ramp fault on a GPS pseudorange measurement. A second contribution is made in determining how augmenting GPS with an ADM compares to using a low-cost IMU. By comparing the results for the GPS-ADM EKF against the GPS-IMU EKF it is found that protection levels for the GPS-ADM EKF were only approximately 2% higher. This indicates that the GPS-ADM EKF may potentially replace the GPS-IMU EKF for integrity monitoring should the IMU ever fail. In this way the ADM may contribute to the navigation system robustness and redundancy. To investigate this further, a third contribution is made in determining whether or not the ADM can function as an IMU replacement to improve navigation system redundancy by investigating the case of three IMU accelerometers failing. It is found that the failed IMU measurements may be supplemented by the ADM and adequate integrity monitoring performance achieved. Besides treating the IMU and ADM separately as in the GPS-IMU EKF and GPS-ADM EKF, a fourth contribution is made in investigating the possibility of fusing the IMU and ADM information together to achieve greater performance than either alone. This is investigated using the GPS-IMU-ADM EKF. It is found that the GPS-IMU-ADM EKF can achieve protection levels approximately 3% lower in the horizontal and 6% lower in the vertical than a GPS-IMU EKF. However this small improvement may not justify the complexity of fusing the IMU with an ADM in practical systems. Affordable ABAS in general aviation may enhance existing GPS-only fault detection solutions or help overcome any outages in augmentation systems such as the Ground-based Regional Augmentation System (GRAS). Countries such as Australia which currently do not have an augmentation solution for general aviation could especially benefit from the economic savings and safety benefits of satellite navigation-based APV approaches.

Automation of an underground mining vehicle using reactive navigation and opportunistic localization

This paper describes the implementation of an autonomous navigation system onto a 30 tonne Load-Haul-Dump truck. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made - a technique we refer to as opportunistic localization. The truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

Autonomous control of underground mining vehicles using reactive navigation

Describes how many of the navigation techniques developed by the robotics research community over the last decade may be applied to a class of underground mining vehicles (LHDs and haul trucks). We review the current state-of-the-art in this area and conclude that there are essentially two basic methods of navigation applicable. We describe an implementation of a reactive navigation system on a 30 tonne LHD which has achieved full-speed operation at a production mine.

Reactive navigation and opportunistic localization for autonomous underground mining vehicles

This paper describes an autonomous navigation system for a large underground mining vehicle. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made – a technique we refer to as opportunistic localization. The paper briefly reviews absolute and relative navigation strategies, and describes an implementation of a reactive navigation system on a 30 tonne Load-Haul-Dump truck. This truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

Mobile robot navigation as a planar visual servoing problem

This paper demonstrates some interesting connections between the hitherto disparate fields of mobile robot navigation and image-based visual servoing. A planar formulation of the well-known image-based visual servoing method leads to a bearing-only navigation system that requires no explicit localization and directly yields desired velocity. The well known benefits of image-based visual servoing such as robustness apply also to the planar case. Simulation results are presented.

Mobile robot navigation as a planar visual servoing problem

This paper demonstrates some interesting connections between the hitherto disparate fields of mobile robot navigation and image-based visual servoing. A planar formulation of the well-known image-based visual servoing method leads to a bearing-only navigation system that requires no explicit localization and directly yields desired velocity. The well known benefits of image-based visual servoing such as robustness apply also to the planar case. Simulation results are presented.

Hybrid robot control and SLAM for persistent navigation and mapping

For a mobile robot to operate autonomously in real-world environments, it must have an effective control system and a navigation system capable of providing robust localization, path planning and path execution. In this paper we describe the work investigating synergies between mapping and control systems. We have integrated development of a control system for navigating mobile robots and a robot SLAM system. The control system is hybrid in nature and tightly coupled with the SLAM system; it uses a combination of high and low level deliberative and reactive control processes to perform obstacle avoidance, exploration, global navigation and recharging, and draws upon the map learning and localization capabilities of the SLAM system. The effectiveness of this hybrid, multi-level approach was evaluated in the context of a delivery robot scenario. Over a period of two weeks the robot performed 1143 delivery tasks to 11 different locations with only one delivery failure (from which it recovered), travelled a total distance of more than 40km, and recharged autonomously a total of 23 times. In this paper we describe the combined control and SLAM system and discuss insights gained from its successful application in a real-world context.

Multi-sensor data fusion for UAV navigation during landing operations

This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

OpenRatSLAM : an open source brain-based SLAM system

RatSLAM is a navigation system based on the neural processes underlying navigation in the rodent brain, capable of operating with low resolution monocular image data. Seminal experiments using RatSLAM include mapping an entire suburb with a web camera and a long term robot delivery trial. This paper describes OpenRatSLAM, an open-source version of RatSLAM with bindings to the Robot Operating System framework to leverage advantages such as robot and sensor abstraction, networking, data playback, and visualization. OpenRatSLAM comprises connected ROS nodes to represent RatSLAM’s pose cells, experience map, and local view cells, as well as a fourth node that provides visual odometry estimates. The nodes are described with reference to the RatSLAM model and salient details of the ROS implementation such as topics, messages, parameters, class diagrams, sequence diagrams, and parameter tuning strategies. The performance of the system is demonstrated on three publicly available open-source datasets.

Examining the effects of an eco-driving system on driver distraction

Driver distraction has recently been defined by Regan as "the diversion of attention away from activities critical for safe driving toward a competing activity, which may result in insufficient or no attention to activities critical for safe driving (Regan, Hallett & Gordon, 2011, p.1780)". One source of distraction is in-vehicle devices, even though they might provide other benefits, e.g. navigation systems. Currently, eco-driving systems have been growing rapidly in popularity. These systems send messages to drivers so that driving performance can be improved in terms of fuel efficiency. However, there remain unanswered questions about whether eco-driving systems endanger drivers by distracting them. In this research, the CARRS-Q advanced driving simulator was used in order to provide safety for participants and meanwhile simulate real world driving. The distraction effects of tasks involving three different in-vehicle systems were investigated: changing a CD, entering a five digit number as a part of navigation task and responding to an eco-driving task. Driving in these scenarios was compared with driving in the absence of these distractions, and while drivers engaged in critical manoeuvres. In order to account for practice effects, the same scenarios were duplicated on a second day. The three in-vehicle systems were not the exact facsimiles of any particular existing system, but were designed to have similar characteristics to those of system available. In general, the results show that drivers’ mental workloads are significantly higher in navigation and CD changing scenarios in comparison to the two other scenarios, which implies that these two tasks impose more visual/manual and cognitive demands. However, eco-driving mental workload is still high enough to be called marginally significant (p ~ .05) across manoeuvres. Similarly, event detection tasks show that drivers miss significantly more events in the navigation and CD changing scenarios in comparison to both the baseline and eco-driving scenario across manoeuvres. Analysis of the practice effect shows that drivers’ baseline scenario and navigation scenario exhibit significantly less demand on the second day. However, the number of missed events across manoeuvres confirmed that drivers can detect significantly more events on the second day for all scenarios. Distraction was also examined separately for five groups of manoeuvres (straight, lane changing, overtaking, braking for intersections and braking for roundabouts), in two locations for each condition. Repeated measures mixed ANOVA results show that reading an eco-driving message can potentially impair driving performance. When comparing the three in–vehicle distractions tested, attending to an eco-driving message is similar in effect to the CD changing task. The navigation task degraded driver performance much more than these other sources of distraction. In lane changing manoeuvres, drivers’ missed response counts degraded when they engaged in reading eco-driving messages at the first location. However, drivers’ event detection abilities deteriorated less at the second lane changing location. In baseline manoeuvres (driving straight), participants’ mean minimum speed degraded more in the CD changing scenario. Drivers’ lateral position shifted more in both CD changing and navigation tasks in comparison with both eco-driving and baseline scenarios, so they were more visually distracting. Participants were better at event detection in baseline manoeuvres in comparison with other manoeuvres. When approaching an intersection, the navigation task caused more events to be missed by participants, whereas eco-driving messages seemed to make drivers less distracted. The eco-driving message scenario was significantly less distracting than the navigation system scenario (fewer missed responses) when participants commenced braking for roundabouts. To sum up, in spite of the finding that two other in-vehicle tasks are more distracting than the eco-driving task, the results indicate that even reading a simple message while driving could potentially lead to missing an important event, especially when executing critical manoeuvres. This suggests that in-vehicle eco-driving systems have the potential to contribute to increased crash risk through distraction. However, there is some evidence of a practice effect which suggests that future research should focus on performance with habitual rather than novel tasks. It is recommended that eco-driving messages be delivered to drivers off-line when possible.

Vision-only autonomous navigation using topometric maps

This paper presents a mapping and navigation system for a mobile robot, which uses vision as its sole sensor modality. The system enables the robot to navigate autonomously, plan paths and avoid obstacles using a vision based topometric map of its environment. The map consists of a globally-consistent pose-graph with a local 3D point cloud attached to each of its nodes. These point clouds are used for direction independent loop closure and to dynamically generate 2D metric maps for locally optimal path planning. Using this locally semi-continuous metric space, the robot performs shortest path planning instead of following the nodes of the graph --- as is done with most other vision-only navigation approaches. The system exploits the local accuracy of visual odometry in creating local metric maps, and uses pose graph SLAM, visual appearance-based place recognition and point clouds registration to create the topometric map. The ability of the framework to sustain vision-only navigation is validated experimentally, and the system is provided as open-source software.

Multi-level information fusion for environment aware robotic navigation

This thesis develops the hardware and software framework for an integrated navigation system. Dynamic data fusion algorithms are used to develop a system with a high level of resistance to the typical problems that affect standard navigation systems.