Visual Inertial Indoor Navigation Systems And Algorithms For Uav Inspection Vehicles

Download Visual Inertial Indoor Navigation Systems And Algorithms For Uav Inspection Vehicles full books in PDF, epub, and Kindle. Read online Visual Inertial Indoor Navigation Systems And Algorithms For Uav Inspection Vehicles ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Visual-Inertial Indoor Navigation Systems and Algorithms for UAV Inspection Vehicles

Author : Marcello Chiaberge
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

DOWNLOAD NOW!

Book Synopsis Visual-Inertial Indoor Navigation Systems and Algorithms for UAV Inspection Vehicles by : Marcello Chiaberge

Download or read book Visual-Inertial Indoor Navigation Systems and Algorithms for UAV Inspection Vehicles written by Marcello Chiaberge and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In UAV navigation, one of the challenges in which considerable efforts are being focused is to be able to move indoors. Completing this challenge would imply being able to respond to a series of industrial market needs such as the inspection of internal environments for safety purpose or the inventory of stored material. Usually GPS is used for navigation, but in a closed or underground environment, its signal is almost never available. As a consequence, to achieve the goal and ensure that the UAV is able to accurately estimate its position and orientation without the usage of GPS, an alternative navigation system based on visual-inertial algorithms and the SLAM will be proposed using data fusion techniques. In addition to the navigation system, we propose an obstacle avoidance method based on a Lidar sensor that allows navigation even in the absence of light.

Indoor Navigation Strategies for Aerial Autonomous Systems

Author : Pedro Castillo-Garcia
Publisher : Butterworth-Heinemann
ISBN 13 : 0128053399
Total Pages : 302 pages
Book Rating : 4.1/5 (28 download)

DOWNLOAD NOW!

Book Synopsis Indoor Navigation Strategies for Aerial Autonomous Systems by : Pedro Castillo-Garcia

Download or read book Indoor Navigation Strategies for Aerial Autonomous Systems written by Pedro Castillo-Garcia and published by Butterworth-Heinemann. This book was released on 2016-11-10 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Indoor Navigation Strategies for Aerial Autonomous Systems presents the necessary and sufficient theoretical basis for those interested in working in unmanned aerial vehicles, providing three different approaches to mathematically represent the dynamics of an aerial vehicle. The book contains detailed information on fusion inertial measurements for orientation stabilization and its validation in flight tests, also proposing substantial theoretical and practical validation for improving the dropped or noised signals. In addition, the book contains different strategies to control and navigate aerial systems. The comprehensive information will be of interest to both researchers and practitioners working in automatic control, mechatronics, robotics, and UAVs, helping them improve research and motivating them to build a test-bed for future projects. Provides substantial information on nonlinear control approaches and their validation in flight tests Details in observer-delay schemes that can be applied in real-time Teaches how an IMU is built and how they can improve the performance of their system when applying observers or predictors Improves prototypes with tactics for proposed nonlinear schemes

Evaluation of a Commercially Available Visual-Inertial Odometry Solution for Indoor Navigation

Author : Ankit Agarwal
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (119 download)

DOWNLOAD NOW!

Book Synopsis Evaluation of a Commercially Available Visual-Inertial Odometry Solution for Indoor Navigation by : Ankit Agarwal

Download or read book Evaluation of a Commercially Available Visual-Inertial Odometry Solution for Indoor Navigation written by Ankit Agarwal and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Heightened public interest in Unmanned Aerial Systems (UAS) has led recently to a rapid increase in both the number and diversity of small- to medium-sized vehicles in the public airspace. With many of these UAS boasting autonomous capabilities such as hands-free flying and obstacle avoidance, safe and accurate autonomous localization and navigation remains critically important. Various technologies have been developed to solve the problem of accurate localization in an unknown airspace, but highly accurate vision-based navigation solutions continue to see rapid development due to the added challenges posed by indoor navigation. Namely, the lack of a reliable GPS connection in indoor environments proves challenging for precise maneuvering, and many of the highest-fidelity alternatives to GPS-based localization are heavy, expensive, and difficult to implement. Growing consumer and commercial adoption of Virtual and Augmented Reality technologies has led to a sharp increase in the number of compact localization solutions available to the public, and the capabilities of these devices conveniently make them choice candidates in solving the challenges of accurate indoor navigation. In the present study, a UAS navigation solution using the Intel RealSense T265, a commercially available Visual-Inertial Odometry (VIO) device, is developed and presented for the purpose of characterizing indoor localization performance. The goal of the study is to determine whether the localization fidelity of a compact and inexpensive VIO solution is sufficiently high to support safe and reliable autonomy of small indoor aerial vehicles. Position and heading data from the T265 are analyzed in their raw form and also after correction using an Extended Kalman Filter (EKF). These data are gathered by way of a hand-carry test, and are compared to ground truth measurements obtained via a Vicon motion capture system. Additionally, a closed-loop flight test is performed outside of a motion capture room for concept validation purposes and to evaluate the convergence and command tracking capability of the EKF-based navigation system. Results from hand-carry testing examined both the raw data from the T265 and the combined data using the EKF. Localization estimates from the device gathered immediately after initialization are highly inaccurate, but the raw data improves significantly as the VIO device continues to operate and gather information about its environment. The device may indeed prove sufficiently accurate for precision maneuvering applications, but only once it has been running for some time. These findings also suggest that the device may perform well when combined with additional sensors (such as LiDAR) that can "correct" the initial pose estimates and reduce the time required to provide an accurate solution. Further localization improvements may also be achievable with varied software configurations. The performance of the Extended Kalman Filter during the closed-loop flight is also evaluated, and while the EKF does not significantly improve position estimates while the raw device data is still inaccurate, it shows smoothing of noisy T265 measurements and generally precise trajectory following capabilities. Future work to extend this characterization shall involve testing the performance of the device across varying flight envelopes, and especially for longer durations.

Algorithms for Unmanned Aerial Vehicle Navigation Systems: Simplified Navigation Algorithms for Small Unmanned Aerial Vehicles

Author : Vladimir Larin
Publisher : Outskirts Press
ISBN 13 : 9781977200648
Total Pages : 206 pages
Book Rating : 4.2/5 (6 download)

DOWNLOAD NOW!

Book Synopsis Algorithms for Unmanned Aerial Vehicle Navigation Systems: Simplified Navigation Algorithms for Small Unmanned Aerial Vehicles by : Vladimir Larin

Download or read book Algorithms for Unmanned Aerial Vehicle Navigation Systems: Simplified Navigation Algorithms for Small Unmanned Aerial Vehicles written by Vladimir Larin and published by Outskirts Press. This book was released on 2019-04-19 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: The algorithms presented in this book were designed to achieve an acceptable trade-off between contradictive requirements to the software of small UAV navigation systems: sufficient accuracy and reliability in order to perform required flight missions on the one hand, and acceptable cost and simplicity of this software on the other hand. The core of modern navigation systems is integrated Strapdown Inertial Navigation System (SINS) and GPS, so in this book, the SINS algorithms and the algorithms of sensor fusion are described primarily. Inertial sensors (rate gyros and accelerometers) used in SINS are manufactured on the basis of the MEMS-technology. That is why they possess poor accuracy and need to be corrected with other sensors (GPS, magnetometers, and barometric altimeters). It is necessary to take into account that flight missions of small UAVs are characterized by small flight distances, small flight times, small flight speeds, etc. These properties of small UAV flight missions and properties of MEMS-sensors create a practical background for simplification of the SINS algorithms, simultaneously preserving their accuracy at acceptable levels. The navigation algorithms for gyro-free SINS are also considered. Increasing reliability of the UAV navigation systems requires a solution of the problems of the detection of the faulty sensors. These algorithms are described. Some practical aspects of the operation of navigation systems such as initial alignment, sensors calibration, and laboratory, ground, and flight testing of integrated SINS for small UAVs are also presented. This book will be useful for a wide circle of researchers, engineers, and graduate students involved in modern UAV design and manufacturing.

Industrial Robotics

Author : Antoni Grau
Publisher : BoD – Books on Demand
ISBN 13 : 1838807330
Total Pages : 178 pages
Book Rating : 4.8/5 (388 download)

DOWNLOAD NOW!

Book Synopsis Industrial Robotics by : Antoni Grau

Download or read book Industrial Robotics written by Antoni Grau and published by BoD – Books on Demand. This book was released on 2020-09-09 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, a new approach to the Industry 4.0 revolution is given. New policies and challenges appear and education in robotics also needs to be adapted to this new era. Together with new factory conceptualization, novel applications introduce new paradigms and new solutions to old problems. The factory opens its walls and outdoor applications are solved with new robot morphologies and new sensors that were unthinkable before Industry 4.0 era. This book presents nine chapters that propose a new outlook for an unstoppable revolution in industrial robotics, from drones to software robots

Vision-aided Inertial Navigation System Design for Indoor Quadrotors

Author : Lianfeng Hou
Publisher :
ISBN 13 :
Total Pages : 97 pages
Book Rating : 4.:/5 (959 download)

DOWNLOAD NOW!

Book Synopsis Vision-aided Inertial Navigation System Design for Indoor Quadrotors by : Lianfeng Hou

Download or read book Vision-aided Inertial Navigation System Design for Indoor Quadrotors written by Lianfeng Hou and published by . This book was released on 2015 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: The navigation task for unmanned aerial vehicles (UAVs), such as quadrotors, in an indoor environment becomes challenging as the global positioning system (GPS) and the magnetometer may provide inaccurate aiding measurements and the signals may get jammed. The navigation system design in this thesis integrates a visual navigation block with a inertial navigation system block, which adds information about aiding measurements information for indoor navigation design. The direct visual measurements are feature coordinates that are obtained from images taken from an onboard monocular camera with different positions in the 3D world space. The scaled relative pose measurements are generated through vision algorithm implementations presented in this thesis. The vehicle states are estimated using the extended Kalman filter (EKF) with inputs from a gyroscope and accelerometer. The EKF sensor fusion process combines inertial measurements and the visual aid- ing measurement to get an optimal estimation. This thesis provides two design results: one navigation system assumes that the 3D world feature coordinates are known and that the navigation system is map-based for the feature ex- traction. The other navigation system does not require prior knowledge of the feature location and captures the feature based on map-less vision algorithms with geometry constraints.

Inertial and Visual Navigation Systems for Autonomous Vehicles

Author : Dipam Chakraborty
Publisher :
ISBN 13 : 9783668881204
Total Pages : 56 pages
Book Rating : 4.8/5 (812 download)

DOWNLOAD NOW!

Book Synopsis Inertial and Visual Navigation Systems for Autonomous Vehicles by : Dipam Chakraborty

Download or read book Inertial and Visual Navigation Systems for Autonomous Vehicles written by Dipam Chakraborty and published by . This book was released on 2018-12-09 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master's Thesis from the year 2018 in the subject Engineering - Robotics, National Institute of Technology, Rourkela, language: English, abstract: Indoor navigation is a challenging task due to the absence of Global Positioning System(GPS). This project removes the need for GPS in systems by combining Inertial Navigation Systems (INS) and Visual Navigation Systems (VNS), with the help of machine learning with Artificial and Convolutional Neural Networks.In GPS denied environments a highly accurate INS is necessary, it must also be coupled with another system to bound the continious drift error that is present in INS, for which VNS is employed. The system was implemented using a ground robot to collect ground truth data, which were used as datasets to train a filter that increases the accuracy of the INS. The accuracy of the INS has been proven on the hardware platfrom over multiple datasets. Eventually Visual Navigation data can also be fed into the same system, which for now is implemented in simulation, as an independent system. A software and hardware framework have been developed that can be used in the future for further developments. The project also optimizes visual navigation for use on low power hardware with hardware acceleration for maximized speed. A low cost and scalable indoor navigation system is developed for indoor navigation, which can also be further extended to Autonomous Underwater Vehicles (AUV) in 3D space.

Pre-integrated Dynamics Factors and a Dynamical Agile Visual-inertial Dataset for UAV Perception

Author : Amado Antonini
Publisher :
ISBN 13 :
Total Pages : 78 pages
Book Rating : 4.:/5 (15 download)

DOWNLOAD NOW!

Book Synopsis Pre-integrated Dynamics Factors and a Dynamical Agile Visual-inertial Dataset for UAV Perception by : Amado Antonini

Download or read book Pre-integrated Dynamics Factors and a Dynamical Agile Visual-inertial Dataset for UAV Perception written by Amado Antonini and published by . This book was released on 2018 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the past few years, the rapid development of unmanned aerial vehicle (UAV) technology has been met by increased interest in these platforms for a wide range of applications. Particularly, the autonomous navigation of these vehicles is of great interest for applications such as surveillance, mapping, searching, agriculture, and film-making, to name a few. But autonomous UAV research has a long way to go to meet the capabilities and robustness required in many of these applications. This work presents two contributions towards closing that gap: pre-integrated dynamics factors for factor graph visual-inertial odometry (VIO), and a large-scale dataset with a great variety of visual, inertial, and dynamical sensor data from a quadrotor platform. The pre-integrated dynamics factors were tested on a challenging subset of the dataset and showed an improvement in robustness of a VIO system. The size and variety of the dataset make it a valuable tool for evaluating and testing visual-inertial estimation algorithms, as shown with the dynamics factors. Both contributions facilitate the development of more robust autonomous UAV navigation systems.

Disturbance Observer-based Motion Control and Visual-inertial-actuator Odometry for UAVs

Author : Amir Moeini
Publisher :
ISBN 13 :
Total Pages : 106 pages
Book Rating : 4.:/5 (131 download)

DOWNLOAD NOW!

Book Synopsis Disturbance Observer-based Motion Control and Visual-inertial-actuator Odometry for UAVs by : Amir Moeini

Download or read book Disturbance Observer-based Motion Control and Visual-inertial-actuator Odometry for UAVs written by Amir Moeini and published by . This book was released on 2021 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motion control of multirotor Unmanned Aerial Vehicles (UAV) is an area of research which continues to generate significant interest in the community. Being able to accurately follow a broad class of trajectories clearly improves the mission capabilities of the vehicle. Model uncertainty and external disturbances are important factors reducing motion control performance. Improving the robustness of motion control can clearly broaden UAV capability. In this thesis we propose a number of trajectory tracking motion controls which are based on a backstepping design method. By incorporating disturbance observers for external force and torque the proposed methods provide exponentially stable tracking error dynamics for the constant disturbance case. For time-varying disturbances tracking error is proven to be ultimately bounded. The stability analysis accounts for the full nonlinear vehicle model which includes translational and rotational dynamics. This avoids having to make common simplifying assumptions typical of designs with inner outer loop structure (e.g., linear approximation of the rotational dynamics) during the closed-loop stability analysis. The proposed design provides a model-based partial compensation of rotor drag. Software-in-the-loop (SITL) simulation and experimental flight testing results are presented. These results show the effectiveness of the proposed method using the commonly used open-source PX4/Pixhawk development framework. The results demonstrate the methods' practical usefulness including their robustness and tracking error performance. The developed motion control algorithms require an accurate knowledge of the system's state, in some applications a description of the environment and an estimate of external forces (e.g., aerial manipulation and load transport). Having an algorithm that only depends on onboard sensors can increase autonomy and reliability. There has been an increasing amount of work developing state estimation algorithms using vision and inertial measurements. However, incorporation of the dynamics modelling and actuation data, which are already available on UAVs and can provide more information about the vehicle's motion, are normally ignored or just an approximate model with unrealistic assumption on force modelling is used. In this thesis, we include an accurate dynamical modelling of a multirotor by considering the effect of rotor drag and also a disturbance observer developed with the assumption of constant force disturbance into an existing open source state estimation approach. The effect of rotor drag is proved to be significant in control and state estimation and its consideration can improve both the estimation and control tasks. In addition, the proposed disturbance observer which is reformulated as a residual term can assist the estimator to differentiate between the constant or slowly time-varying component of the external force and the accelerometer bias providing a more accurate force estimate which is a need in many UAVs applications. Furthermore, this structure increases the odometry accuracy. We evaluate the performance of our proposed method by integrating it with an open source Visual-Inertial Odometry (VIO) system and testing it on benchmark datasets. The results show a significant improvement in the estimation accuracy.

Vision Based Systemsfor UAV Applications

Author : Aleksander Nawrat
Publisher : Springer
ISBN 13 : 3319003690
Total Pages : 348 pages
Book Rating : 4.3/5 (19 download)

DOWNLOAD NOW!

Book Synopsis Vision Based Systemsfor UAV Applications by : Aleksander Nawrat

Download or read book Vision Based Systemsfor UAV Applications written by Aleksander Nawrat and published by Springer. This book was released on 2013-12-06 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is motivated by a significant number of vision based algorithms for Unmanned Aerial Vehicles (UAV) that were developed during research and development projects. Vision information is utilized in various applications like visual surveillance, aim systems, recognition systems, collision-avoidance systems and navigation. This book presents practical applications, examples and recent challenges in these mentioned application fields. The aim of the book is to create a valuable source of information for researchers and constructors of solutions utilizing vision from UAV. Scientists, researchers and graduate students involved in computer vision, image processing, data fusion, control algorithms, mechanics, data mining, navigation and IC can find many valuable, useful and practical suggestions and solutions. The latest challenges for vision based systems are also presented.

Imaging and Sensing for Unmanned Aircraft Systems

Author : Vania V. Estrela
Publisher : Institution of Engineering and Technology
ISBN 13 : 1785616420
Total Pages : 361 pages
Book Rating : 4.7/5 (856 download)

DOWNLOAD NOW!

Book Synopsis Imaging and Sensing for Unmanned Aircraft Systems by : Vania V. Estrela

Download or read book Imaging and Sensing for Unmanned Aircraft Systems written by Vania V. Estrela and published by Institution of Engineering and Technology. This book was released on 2020-02-01 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume book set explores how sensors and computer vision technologies are used for the navigation, control, stability, reliability, guidance, fault detection, self-maintenance, strategic re-planning and reconfiguration of unmanned aircraft systems (UAS). Volume 1 concentrates on UAS control and performance methodologies including Computer Vision and Data Storage, Integrated Optical Flow for Detection and Avoidance Systems, Navigation and Intelligence, Modeling and Simulation, Multisensor Data Fusion, Vision in Micro-Aerial Vehicles (MAVs), Computer Vision in UAV using ROS, Security Aspects of UAV and Robot Operating System, Vision in Indoor and Outdoor Drones, Sensors and Computer Vision, and Small UAV for Persistent Surveillance. Volume 2 focuses on UAS deployment and applications including UAV-CPSs as a Testbed for New Technologies and a Primer to Industry 5.0, Human-Machine Interface Design, Open Source Software (OSS) and Hardware (OSH), Image Transmission in MIMO-OSTBC System, Image Database, Communications Requirements, Video Streaming, and Communications Links, Multispectral vs Hyperspectral Imaging, Aerial Imaging and Reconstruction of Infrastructures, Deep Learning as an Alternative to Super Resolution Imaging, and Quality of Experience (QoE) and Quality of Service (QoS).

Navigation and Mapping for Aerial Vehicles Based on Inertial and Imaging Sensors

Author :
Publisher :
ISBN 13 : 9789175195537
Total Pages : 82 pages
Book Rating : 4.1/5 (955 download)

DOWNLOAD NOW!

Book Synopsis Navigation and Mapping for Aerial Vehicles Based on Inertial and Imaging Sensors by :

Download or read book Navigation and Mapping for Aerial Vehicles Based on Inertial and Imaging Sensors written by and published by . This book was released on 2013 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Small and medium sized Unmanned Aerial Vehicles (UAV) are today used in military missions, and will in the future find many new application areas such as surveillance for exploration and security. To enable all these foreseen applications, the UAV's have to be cheap and of low weight, which restrict the sensors that can be used for navigation and surveillance. This thesis investigates several aspects of how fusion of navigation and imaging sensors can improve both tasks at a level that would require much more expensive sensors with the traditional approach of separating the navigation system from the applications. The core idea is that vision sensors can support the navigation system by providing odometric information of the motion, while the navigation system can support the vision algorithms, used to map the surrounding environment, to be more efficient. The unified framework for this kind of approach is called Simultaneous Localisation and Mapping (SLAM) and it will be applied here to inertial sensors, radar and optical camera.

Indoor Navigation for Unmanned Aerial Vehicles

Author :
Publisher :
ISBN 13 :
Total Pages : 30 pages
Book Rating : 4.:/5 (495 download)

DOWNLOAD NOW!

Book Synopsis Indoor Navigation for Unmanned Aerial Vehicles by :

Download or read book Indoor Navigation for Unmanned Aerial Vehicles written by and published by . This book was released on 2009 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability for vehicles to navigate unknown environments is critical for autonomous operation. Mapping of a vehicle's environment and self-localization within that environment are especially difficult for an Unmanned Aerial Vehicle (UAV) due to the complexity of UAV attitude and motion dynamics, as well as interference from external influences such as wind. By using a stable vehicle platform and taking advantage of the geometric structure typical of most indoor environments, the complexity of the localization and mapping problem can be reduced. Interior wall and obstacle location can be measured using low-cost range sensors. Relative vehicle location within the mapped environment can then be determined. By alternating between mapping and localization, a vehicle can explore its environment autonomously. This paper examines available low-cost range sensors for suitability in solving the mapping and localization problem. A control system and navigation algorithm are developed to perform mapping of indoor environments and localization. Simulation and experimental results are provided to determine feasibility of the proposed approach to indoor navigation.

Vision-aided Navigation for Autonomous Vehicles Using Tracked Feature Points

Author : Ahmed Saber Soliman Sayem
Publisher :
ISBN 13 :
Total Pages : 164 pages
Book Rating : 4.:/5 (959 download)

DOWNLOAD NOW!

Book Synopsis Vision-aided Navigation for Autonomous Vehicles Using Tracked Feature Points by : Ahmed Saber Soliman Sayem

Download or read book Vision-aided Navigation for Autonomous Vehicles Using Tracked Feature Points written by Ahmed Saber Soliman Sayem and published by . This book was released on 2016 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis discusses the evaluation, implementation, and testing of several navigation algorithms and feature extraction algorithms using an inertial measurement unit (IMU) and an image capture device (camera) mounted on a ground robot and a quadrotor UAV. The vision-aided navigation algorithms are implemented on data-collected from sensors on an unmanned ground vehicle and a quadrotor, and the results are validated by comparison with GPS data. The thesis investigates sensor fusion techniques for integrating measured IMU data with information extracted from image processing algorithms in order to provide accurate vehicle state estimation. This image-based information takes the forms of features, such as corners, that are tracked over multiple image frames. An extended Kalman filter (EKF) in implemented to fuse vision and IMU data. The main goal of the work is to provide navigation of mobile robots in GPS-denied environments such as indoor environments, cluttered urban environments, or space environments such as asteroids, other planets or the moon. The experimental results show that combining pose information extracted from IMU readings along with pose information extracted from a vision-based algorithm managed to solve the drift problem that comes from using IMU alone and the scale problem that comes from using a monocular vision-based algorithm alone.

Autonomous Visual-Inertial Navigation for Quadrotor MAVs

Author : Shehryar Khurshid
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (133 download)

DOWNLOAD NOW!

Book Synopsis Autonomous Visual-Inertial Navigation for Quadrotor MAVs by : Shehryar Khurshid

Download or read book Autonomous Visual-Inertial Navigation for Quadrotor MAVs written by Shehryar Khurshid and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this thesis is to develop a system which would enable a quadrotor MAV (Micro Aerial Vehicle) to estimate its position and orientation and to autonomously navigate in unknown environments using vision as the primary source of information. To navigate in three-dimensional space, an autonomous MAV should not only possess knowledge of its current position and orientation (pose for short), but also of the world around it. While the former can be obtained using a GPS for large outdoor environments and the latter can be provided as a map, a truly autonomous navigation system should enable an MAV to infer its pose in indoor, GPS-denied environments using only the on-board sensors. While images from a camera are rich in data, they are devoid of any depth information. Extracting depth information from a single camera therefore requires the presence of reference objects with known geometry such as artificial fiducial markers in the field of view, or state-of-the-art monocular structure from motion techniques. In this thesis, we will study and develop solutions for environments which the MAV possesses no a priori information. We will present our modular approach to the problem of autonomous navigation which comprises of three separate blocks. The first block uses a state-of-the-art monocular simultaneous localization and mapping algorithm to transform the camera into a real time pose sensor. The second block uses an extended Kalman filter to refine the pose information from the camera by fusing it with data from the MAV's onboard sensors. The third block uses a proportionalintegral- derivative controller to generate control commands for the MAV. We implemented our system on a commercially available quadrotor MAV and tested it in real world scenarios. The accuracy of our system will be compared against a highly accurate motion capture system and the findings will be presented/analyzed.

Vision-Aided Inertial Navigation

Author : Chiara Troiani
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (991 download)

DOWNLOAD NOW!

Book Synopsis Vision-Aided Inertial Navigation by : Chiara Troiani

Download or read book Vision-Aided Inertial Navigation written by Chiara Troiani and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate egomotion estimation is of utmost importance for any navigation system.Nowadays di_erent sensors are adopted to localize and navigate in unknownenvironments such as GPS, range sensors, cameras, magnetic field sensors, inertialsensors (IMU). In order to have a robust egomotion estimation, the information ofmultiple sensors is fused. Although the improvements of technology in providingmore accurate sensors, and the efforts of the mobile robotics community in thedevelopment of more performant navigation algorithms, there are still openchallenges. Furthermore, the growing interest of the robotics community in microrobots and swarm of robots pushes towards the employment of low weight, low costsensors and low computational complexity algorithms. In this context inertial sensorsand monocular cameras, thanks to their complementary characteristics, low weight,low cost and widespread use, represent an interesting sensor suite.This dissertation represents a contribution in the framework of vision-aided inertialnavigation and tackles the problems of data association and pose estimation aimingfor low computational complexity algorithms applied to MAVs.For what concerns the data association, a novel method to estimate the relative motionbetween two consecutive camera views is proposed. It only requires the observationof a single feature in the scene and the knowledge of the angular rates from an IMU,under the assumption that the local camera motion lies in a plane perpendicular to thegravity vector. Two very efficient algorithms to remove the outliers of the featurematchingprocess are provided under the abovementioned motion assumption. Inorder to generalize the approach to a 6DoF motion, two feature correspondences andgyroscopic data from IMU measurements are necessary. In this case, two algorithmsare provided to remove wrong data associations in the feature-matching process. Inthe case of a monocular camera mounted on a quadrotor vehicle, motion priors fromIMU are used to discard wrong estimations.For what concerns the pose estimation problem, this thesis provides a closed formsolution which gives the system pose from three natural features observed in a singlecamera image, once the roll and the pitch angles are obtained by the inertialmeasurements under the planar ground assumption.In order to tackle the pose estimation problem in dark or featureless environments, asystem equipped with a monocular camera, inertial sensors and a laser pointer isconsidered. The system moves in the surrounding of a planar surface and the laserpointer produces a laser spot on the abovementioned surface. The laser spot isobserved by the monocular camera and represents the only point feature considered.Through an observability analysis it is demonstrated that the physical quantities whichcan be determined by exploiting the measurements provided by the aforementionedsensor suite during a short time interval are: the distance of the system from the planarsurface; the component of the system speed that is orthogonal to the planar surface;the relative orientation of the system with respect to the planar surface; the orientationof the planar surface with respect to the gravity. A simple recursive method toperform the estimation of all the aforementioned observable quantities is provided.All the contributions of this thesis are validated through experimental results usingboth simulated and real data. Thanks to their low computational complexity, theproposed algorithms are very suitable for real time implementation on systems withlimited on-board computation resources. The considered sensor suite is mounted on aquadrotor vehicle but the contributions of this dissertations can be applied to anymobile device.

Inertial Navigation Aided by Simultaneous Localization and Mapping

Author : V. Sazdovski
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (835 download)

DOWNLOAD NOW!

Book Synopsis Inertial Navigation Aided by Simultaneous Localization and Mapping by : V. Sazdovski

Download or read book Inertial Navigation Aided by Simultaneous Localization and Mapping written by V. Sazdovski and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned aerial vehicles technologies are getting smaller and cheaper to use and the challenges of payload limitation in unmanned aerial vehicles are being overcome. Integrated navigation system design requires selection of set of sensors and computation power that provides reliable and accurate navigation parameters (position, velocity and attitude) with high update rates and bandwidth in small and cost effective manner. Many of today's operational unmanned aerial vehicles navigation systems rely on inertial sensors as a primary measurement source. Inertial Navigation alone however suffers from slow divergence with time. This divergence is often compensated for by employing some additional source of navigation information external to Inertial Navigation. From the 1990's to the present day Global Positioning System has been the dominant navigation aid for Inertial Navigation. In a number of scenarios, Global Positioning System measurements may be completely unavailable or they simply may not be precise (or reliable) enough to be used to adequately update the Inertial Navigation hence alternative methods have seen great attention. Aiding Inertial Navigation with vision sensors has been the favoured solution over the past several years. Inertial and vision sensors with their complementary characteristics have the potential to answer the requirements for reliable and accurate navigation parameters. In this thesis we address Inertial Navigation position divergence. The information for updating the position comes from combination of vision and motion. When using such a combination many of the difficulties of the vision sensors (relative depth, geometry and size of objects, image blur and etc.) can be circumvented. Motion grants the vision sensors with many cues that can help better to acquire information about the environment, for instance creating a precise map of the environment and localize within the environment. We propose changes to the Simultaneous Localization and Mapping augmented state vector in order to take repeated measurements of the map point. We show that these repeated measurements with certain manoeuvres (motion) around or by the map point are crucial for constraining the Inertial Navigation position divergence (bounded estimation error) while manoeuvring in vicinity of the map point. This eliminates some of the uncertainty of the map point estimates i.e. it reduces the covariance of the map points estimates. This concept brings different parameterization (feature initialisation) of the map points in Simultaneous Localization and Mapping and we refer to it as concept of aiding Inertial Navigation by Simultaneous Localization and Mapping. We show that making such an integrated navigation system requires coordination with the guidance and control measurements and the vehicle task itself for performing the required vehicle manoeuvres (motion) and achieving better navigation accuracy. This fact brings new challenges to the practical design of these modern jam proof Global Positioning System free autonomous navigation systems. Further to the concept of aiding Inertial Navigation by Simultaneous Localization and Mapping we have investigated how a bearing only sensor such as single camera can be used for aiding Inertial Navigation. The results of the concept of Inertial Navigation aided by Simultaneous Localization and Mapping were used. New parameterization of the map point in Bearing Only Simultaneous Localization and Mapping is proposed. Because of the number of significant problems that appear when implementing the Extended Kalman Filter in Inertial Navigation aided by Bearing Only Simultaneous Localization and Mapping other algorithms such as Iterated Extended Kalman Filter, Unscented Kalman Filter and Particle Filters were implemented. From the results obtained, the conclusion can be drawn that the nonlinear filters should be the choice of estimators for this application.