Vision-Based Monocular SLAM in Micro Aerial Vehicle

Micro Aerial Vehicles (MAVs) are popular for their efficiency, agility, and lightweights. They can navigate in dynamic environments that cannot be accessed by humans or traditional aircraft. These MAVs rely on GPS and it will be difficult for GPS-denied areas where it is obstructed by buildings and other obstacles.  Simultaneous Localization and Mapping (SLAM) in an unknown environment can solve the aforementioned problems faced by flying robots.  A rotation and scale invariant visual-based solution, oriented fast and rotated brief (ORB-SLAM) is one of the best solutions for localization and mapping using monocular vision.  In this paper, an ORB-SLAM3 has been used to carry out the research on localizing micro-aerial vehicle Tello and mapping an unknown environment.  The effectiveness of ORB-SLAM3 was tested in a variety of indoor environments.   An integrated adaptive controller was used for an autonomous flight that used the 3D map, produced by ORB-SLAM3 and our proposed novel technique for robust initialization of the SLAM system during flight.  The results show that ORB-SLAM3 can provide accurate localization and mapping for flying robots, even in challenging scenarios with fast motion, large camera movements, and dynamic environments.  Furthermore, our results show that the proposed system is capable of navigating and mapping challenging indoor situations

Nonvisible Satellite Estimation Algorithm for Improved UAV Navigation in Mountainous Regions

This paper presents a very simple and computationally efficient algorithm for the calculation of the occlusion points of a scene, observed from a given point of view. This algorithm is used to calculate, in any point of a control volume, the number of visible satellites and the Dilution Of Precision (DOP). Knowledge of these information is extremely important to reject measurements of non-visible satellites and for the reconstruction of a fictitious Digital Elevation Map (DEM), that envelops all the regions characterized by a number of visible satellites lower than a given threshold. This DEM evolves in time according to the platform motion and satellite dynamics. Because of this time dependency, the Digital Morphing Map (DMM) has been defined. When the DMM is available, it can be used by the path planning algorithm to optimise the platform trajectory in order to avoid regions where the number of visible satellites is dramatically reduced, the DOP value is very high and the risk to receive corrupted measurement is large. In this paper also presents the concept of a Safety Bubble Obstacle Avoidance (SBOA) system. This technique takes advantage from the numerical properties of the covariance matrix defined in the Kalman filtering process. A space and time safety bubble is defined according to the DOP value and is used to automatically determine a minimum fly distance from the surrounding obstacles

Odometria visual monocular em robôs para a agricultura com camara(s) com lentes "olho de peixe"

One of the main challenges in robotics is to develop accurate localization methods that achieve acceptable runtime performances.One of the most common approaches is to use Global Navigation Satellite System such as GPS to localize robots.However, satellite signals are not full-time available in some kind of environments.The purpose of this dissertation is to develop a localization system for a ground robot.This robot is inserted in a project called RoMoVi and is intended to perform tasks like crop monitoring and harvesting in steep slope vineyards.This vineyards are localized in the Douro region which are characterized by the presence of high hills.Thus, the context of RoMoVi is not prosperous for the use of GPS-based localization systems.Therefore, the main goal of this work is to create a reliable localization system based on vision techniques and low cost sensors.To do so, a Visual Odometry system will be used.The concept of Visual Odometry is equivalent to wheel odometry but it has the advantage of not suffering from wheel slip which is present in these kind of environments due to the harsh terrain conditions.Here, motion is tracked computing the homogeneous transformation between camera frames, incrementally.However, this approach also presents some open issues.Most of the state of art methods, specially those who present a monocular camera system, don't perform good motion estimations in pure rotations.In some of them, motion even degenerates in these situations.Also, computing the motion scale is a difficult task that is widely investigated in this field.This work is intended to solve these issues.To do so, fisheye lens cameras will be used in order to achieve wide vision field of views

Carnegie Mellon Team Tartan: Mission-level Robustness with Rapidly Deployed Autonomous Aerial Vehicles in the MBZIRC 2020

For robotics systems to be used in high risk, real-world situations, they have to be quickly deployable and robust to environmental changes, under-performing hardware, and mission subtask failures. Robots are often designed to consider a single sequence of mission events, with complex algorithms lowering individual subtask failure rates under some critical constraints. Our approach is to leverage common techniques in vision and control and encode robustness into mission structure through outcome monitoring and recovery strategies, aided by a system infrastructure that allows for quick mission deployments under tight time constraints and no central communication. We also detail lessons in rapid field robotics development and testing. Systems were developed and evaluated through real-robot experiments at an outdoor test site in Pittsburgh, Pennsylvania, USA, as well as in the 2020 Mohamed Bin Zayed International Robotics Challenge. All competition trials were completed in fully autonomous mode without RTK-GPS. Our system led to 4th place in Challenge 2 and 7th place in the Grand Challenge, and achievements like popping five balloons (Challenge 1), successfully picking and placing a block (Challenge 2), and dispensing the most water autonomously with a UAV of all teams onto an outdoor, real fire (Challenge 3).Comment: 28 pages, 26 figures. To appear in Field Robotics, Special Issues on MBZIRC 202

Analysis and mitigation of site-dependent effects in static and kinematic GNSS applications

Satellitensignale unterliegen auf ihrem Weg von der Satelliten- zur Empfangsantenne einer Vielzahl an Einflüssen die zu Abweichungen führen. Heutzutage stellen in vielen Anwendungsbereichen insbesondere die stationsspezifischen Anteile, welche sich in Mehrwegeeffekte aus dem Fernfeld, NLOS-Empfang und Signalbeugung, den Einfluss der Satellitengeometrie und Antennennahfeldeffekte untergliedern lassen, einen der genauigkeitsbegrenzenden Faktoren in der satellitengestützten Positionsbestimmung dar. Dies ist dadurch begründet, dass durch die Abhängigkeit von der individuell vorliegenden Antennenumgebung eine Minimierung der Einflüsse erheblich erschwert wird und etablierte Strategien, wie beispielsweise die Differenzbildung in relativen Positionierungsansätzen, in der Regel nicht anwendbar sind. Obwohl diese Effekte bereits seit den frühesten Entwicklungen auf dem Gebiet der satellitengestützten Positionsbestimmung untersucht wurden, ist eine vollumfängliche Lösungsstrategie auch in der heutigen Zeit noch nicht verfügbar. Daher hat diese Thematik nicht an Relevanz verloren und es besteht noch immer der Bedarf an weiteren Untersuchungen zur Vertiefung des Verständnisses und zur Erweiterung des Portfolios an verfügbaren Minimierungsansätzen. In dieser Arbeit werden die vier unterschiedlichen Effekte vor dem Hintergrund der hochpräzisen Positionsbestimmung in statischen und kinematischen GNSS-Anwendungen adressiert. Der wesentliche Fokus der Untersuchungen liegt hierbei auf der Detektion und Elimination betroffener Satellitensignale durch die Einbindung detaillierter Umgebungsmodelle aus terrestrischen Messverfahren. Auf Basis dieser methodischen und empirischen Analysen lassen sich für die einzelnen Effekte vier Hauptaspekte herausstellen: (1) Da Antennennahfeldeffekte primär den Messsensor selbst beeinflussen und folglich die angestrebte Detektion und Elimination zur Minimierung nicht geeignet ist, wird alternativ die Minimierung des Einflusses durch spezielle Antennenaufbauten empirisch analysiert. Daraus resultierend werden mit exakt identischen Antennenaufbauten erreichbare Genauigkeiten im Submillimeterbereich nachgewiesen. (2) Der Einfluss auf die Positionsgenauigkeit der potentiell durch eine Signalelimination hervorgerufenen Verschlechterung der Satellitengeometrie kann durch Simulationen generischer Abschattungsszenarien als unkritisch identifiziert werden. Darüber hinaus wird eine Methode zur Integration der Qualität der Satellitengeometrie in die Wegpunktplanung von UAVs entwickelt, welche sowohl in der Planungsphase, als auch während des UAV-Fluges eine Anpassung und Optimierung der Flugroute ermöglicht. (3) Auf Basis mittels terrestrischer Laserscanner erzeugter Punktwolken wird eine Methode zur Erzeugung von Elevationsmasken entwickelt, welche adaptiv gegenüber der vorliegenden Antennenumgebung sind und eine effektive Detektion und Elimination von Satellitensignalen erlauben, die NLOS-Empfang oder Signalbeugung unterliegen. Diese Minimierungsstrategie ist sowohl in statischen, als auch kinematischen Anwendungen einsetzbar und ermöglicht bei zusätzlicher Einbindung von Fresnel Zonen auch die Berücksichtigung der Ausbreitungseigenschaften elektromagnetischer Wellen. (4) Als vorbereitender Schritt für die Entwicklung von Methoden zur Detektion und Eliminierung von Fernfeld-Mehrwegeeffekten werden die Voraussetzungen für die Entstehung der Effekte untersucht. Durch Vergleich simulierter und beobachteter SNR-Zeitreihen und der Berücksichtigung von Fresnel Zonen kann eine Überlappung von 50% zwischen Fresnel-Zone und Reflektorfläche als bereits ausreichend für eine potentielle Mehrwegebelastung identifiziert werden. In der Gesamtbetrachtung liefern die in dieser Arbeit gewonnenen Erkenntnisse und entwickelten Methoden einen relevanten Beitrag zu dem übergeordneten Ziel einer ganzheitlichen Minimierung stationsspezifischer Abweichungen und ermöglichen so eine signifikante Verbesserung der Positionsgenauigkeit unter schwierigen GNSS-Bedingungen. Darüber hinaus nimmt diese Arbeit den in den letzten Jahren forcierten Trend von einer punktweisen zu einer flächenhaften Objekterfassung an, indem das Potenzial einer detaillierten und effizienten Erfassung der Antennenumgebung mittels terrestrischer Laserscanner zur Minimierung und Analyse stationsspezifischer Abweichungen bei der satellitengestützten Positionsbestimmung aufzeigt und genutzt wird.Satellite signals are subject to various error sources on their way from the satellite to the receiving antenna. Nowadays, in many fields of application, the site-dependent parts, which can be separated into far-field multipath, NLOS reception and signal diffraction, the influence of the satellite geometry and antenna near-field effects, are one of the accuracy limiting factors in satellite-based positioning. This is due to the fact that the dependence on the individual antenna environment considerably impedes a minimization of the influences and established strategies, such as double-differencing in relative positioning approaches, are generally not applicable. Although these effects have been subject to scientific research since the earliest developments in the field of satellite-based positioning, an all-embracing solution is still lacking. Therefore, this topic has not lost its relevance and there is still a need for further investigations to deepen the understanding and expanding the portfolio of available mitigation techniques. In this dissertation, the four different effects are addressed against the background of high-precision static and kinematic GNSS applications. In this context, the main focus of the investigations is on the detection and exclusion of affected satellite signals, by integrating detailed environment models derived from terrestrial measurements. Based on these methodological and empirical analyses, four main aspects can be highlighted for the different effects: (1) Since antenna near-field effects primarily affect the measuring sensor itself, and thus, the striven detection and exclusion for mitigation is not applicable in this case, alternatively the mitigation of the influence by special antenna setups is empirically analyzed. As a result, achievable accuracies in the sub-millimeter range can be demonstrated using exactly identical antenna setups. (2) By simulating generic obstruction scenarios, the influence on the positional accuracy of the deterioration of the satellite geometry, potentially caused by an elimination of satellite signals, can be identified as uncritical. Furthermore, a method for integrating measures for the quality of the satellite geometry in the waypoint planning of UAVs is developed, which enables the adaption and optimization of the flight route in the planning phase, as well as during the UAV flight. (3) Based on point clouds of terrestrial laser scanners, a method for the determination of elevation masks that are adaptive to the present antenna environment is developed, which enables an effective detection and exclusion of signals that are subject to NLOS reception or signal diffraction. This mitigation strategy can be applied to static and kinematic GNSS applications and by additionally integrating Fresnel zones, also the propagation characteristics of electromagnetic waves are considered. (4) As a preparatory step for the development of methods for detecting and excluding far-field multipath, the prerequisites for the occurrence of the effect are investigated. By comparison of simulated and observed SNR time series and by considering Fresnel zones, an overlap of 50% between Fresnel zone and reflecting surface can be identified as already being sufficient for potential far-field multipath influences. In the overall view, the findings and methods developed in this dissertation represent a relevant contribution to the superordinate goal of a holistic mitigation of site-dependent effects, and thus, enable a significant improvement of the positional accuracy under difficult GNSS conditions. In addition, this thesis adopts the currently forced trend from a pointwise to an area-based object acquisition by revealing and exploiting the potential of a detailed and efficient acquisition of the antenna environment by terrestrial laser scanners for mitigating and analyzing site-dependent effects in satellite based positioning applications

Radio-Frequency Localization of Multiple Partial Discharges Sources with Two Receivers

Spatial localization of emitting sources is especially interesting in different fields of application. The focus of an earthquake, the determination of cracks in solid structures, or the position of bones inside a body are some examples of the use of multilateration techniques applied to acoustic and vibratory signals. Radar, GPS and wireless sensors networks location are based on radiofrequency emissions and the techniques are the same as in the case of acoustic emissions. This paper is focused on the determination of the position of sources of partial discharges in electrical insulation for maintenance based on the condition of the electrical equipment. The use of this phenomenon is a mere example of the capabilities of the proposed method but it is very representative because the emission can be electromagnetic in the VHF and UHF ranges or acoustic. This paper presents a method to locate more than one source in space with only two receivers, one of them in a fixed position and the other describing a circumference around the first one. The signals arriving from the different sources to the antennas are first separated using a classification technique based on their spectral components. Then, the individualized time differences of arrival (TDOA) from the sources collected at different angles describe a function, angle versus TDOA, that has all the geometric information needed to locate the source. The paper will show how to derive these functions for any source analytically with the position of the source as unknown parameters. Then, it will be demonstrated that it is possible to fit the curve with experimental measurements of the TDOA to obtain the parameters of the position of each source. Finally, the technique is extended to the localization of the emitter in three dimensions.The work done in this paper has been funded by the Spanish Government (MINECO) and the European Regional Development Fund (ERDF) under contract DPI2015-66478-C2-1-R (MINECO/FEDER, UE)

Real-Time Multi-Fisheye Camera Self-Localization and Egomotion Estimation in Complex Indoor Environments

In this work a real-time capable multi-fisheye camera self-localization and egomotion estimation framework is developed. The thesis covers all aspects ranging from omnidirectional camera calibration to the development of a complete multi-fisheye camera SLAM system based on a generic multi-camera bundle adjustment method

UAV-Enabled Surface and Subsurface Characterization for Post-Earthquake Geotechnical Reconnaissance

Major earthquakes continue to cause significant damage to infrastructure systems and the loss of life (e.g. 2016 Kaikoura, New Zealand; 2016 Muisne, Ecuador; 2015 Gorkha, Nepal). Following an earthquake, costly human-led reconnaissance studies are conducted to document structural or geotechnical damage and to collect perishable field data. Such efforts are faced with many daunting challenges including safety, resource limitations, and inaccessibility of sites. Unmanned Aerial Vehicles (UAV) represent a transformative tool for mitigating the effects of these challenges and generating spatially distributed and overall higher quality data compared to current manual approaches. UAVs enable multi-sensor data collection and offer a computational decision-making platform that could significantly influence post-earthquake reconnaissance approaches. As demonstrated in this research, UAVs can be used to document earthquake-affected geosystems by creating 3D geometric models of target sites, generate 2D and 3D imagery outputs to perform geomechanical assessments of exposed rock masses, and characterize subsurface field conditions using techniques such as in situ seismic surface wave testing. UAV-camera systems were used to collect images of geotechnical sites to model their 3D geometry using Structure-from-Motion (SfM). Key examples of lessons learned from applying UAV-based SfM to reconnaissance of earthquake-affected sites are presented. The results of 3D modeling and the input imagery were used to assess the mechanical properties of landslides and rock masses. An automatic and semi-automatic 2D fracture detection method was developed and integrated with a 3D, SfM, imaging framework. A UAV was then integrated with seismic surface wave testing to estimate the shear wave velocity of the subsurface materials, which is a critical input parameter in seismic response of geosystems. The UAV was outfitted with a payload release system to autonomously deliver an impulsive seismic source to the ground surface for multichannel analysis of surface waves (MASW) tests. The UAV was found to offer a mobile but higher-energy source than conventional seismic surface wave techniques and is the foundational component for developing the framework for fully-autonomous in situ shear wave velocity profiling.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145793/1/wwgreen_1.pd