A Photogrammetry-Based Hybrid System for Dynamic Tracking and Measurement

Noncontact measurements of lightweight flexible aerospace structures present several challenges. Objects are usually mounted on a test stand because current noncontact measurement techniques require that the net motion of the object be zero. However, it is often desirable to take measurements of the object under operational conditions, and in the case of miniature aerial vehicles (MAVs) and deploying space structures, the test article will undergo significant translational motion. This thesis describes a hybrid noncontact measurement system which will enable measurement of structural kinematics of an object freely moving about a volume. By using a real-time videogrammetry system, a set of pan-tilt-zoom (PTZ) cameras is coordinated to track large-scale net motion and produce high-speed, high-quality images for photogrammetric surface reconstruction. The design of the system is presented in detail. A method of generating the calibration parameters for the PTZ cameras is presented and evaluated and is shown to produce good results. The results of camera synchronization tests and tracking accuracy evaluation are presented as well. Finally, a demonstration of the hybrid system is presented in which all four PTZ cameras track an MAV in flight

Performance of a Monocular Vision-aided Inertial Navigation System for a Small UAV

DOI: http://dx.doi.org/10.2514/6.2013-4699The use of optical sensors for navigation on aircraft has receive much attention recently. Optical sensors provide a wealth of information about the environment and are standard payloads for many unmanned aerial vehicles (UAVs). Simultaneous localization and map- ping (SLAM) algorithms using optical sensors have become computationally feasible in real time in the last ten years. However, implementations of visual SLAM navigation systems on aerial vehicles are still new and consequently are often limited to restrictive environ- ments or idealized conditions. One example of a ight condition which can dramatically a ect navigation performance is altitude. This paper seeks to examine the performance of monocular extended Kalman lter based SLAM (EKF-SLAM) navigation over a large altitude change. Simulation data is collected which illustrates the behavior of the naviga- tion system over the altitude range. Navigation and control system parameters values are speci ed which improve vehicle performance across the ight conditions. Additionally, a detailed presentation of the monocular EKF-SLAM navigation system is given. Flight test results are presented on a quadrotor

Monocular Visual Mapping for Obstacle Avoidance on UAVs

Copyright © 2013 IEEEDOI: http://dx.doi.org/10.1109/ICUAS.2013.6564722An unmanned aerial vehicle requires adequate knowledge of its surroundings in order to operate in close proximity to obstacles. UAVs also have strict payload and power constraints which limit the number and variety of sensors available to gather this information. It is desirable, therefore, to enable a UAV to gather information about potential obstacles or interesting landmarks using common and lightweight sensor systems. This paper presents a method of fast terrain mapping with a monocular camera. Features are extracted from camera images and used to update a sequential extended Kalman filter. The features locations are parameterized in inverse depth to enable fast depth convergence. Converged features are added to a persistent terrain map which can be used for obstacle avoidance and additional vehicle guidance. Simulation results and results from recorded flight test data are presented to validate the algorithm

Monocular Visual Mapping for Obstacle Avoidance on UAVs

Copyright © 2014 SpringerDOI: http://dx.doi.org/10.1007/s10846-013-9967-7An unmanned aerial vehicle requires adequate knowledge of its surroundings in order to operate in close proximity to obstacles. UAVs also have strict payload and power constraints which limit the number and variety of sensors available to gather this information. It is desirable, therefore, to enable a UAV to gather information about potential obstacles or interesting landmarks using common and lightweight sensor systems. This paper presents a method of fast terrain mapping with a monocular camera. Features are extracted from camera images and used to update a sequential extended Kalman filter. The features locations are parameterized in inverse depth to enable fast depth convergence. Converged features are added to a persistent terrain map which can be used for obstacle avoidance and additional vehicle guidance. Simulation results, results from recorded flight test data, and flight test results are presented to validate the algorithm

Georgia Tech Team Entry for the 2011 AUVSI International Aerial Robotics Competition

Presented at the Third International Aerial Robotics Symposium (IASR), 2011.his paper describes the details of a Quadrotor Unmanned Aerial Vehicle capable of exploring cluttered indoor areas without relying on any external navigational aids. An elaborate Simultaneous Localization and Mapping (SLAM) algorithm is used to fuse information from a laser range sensor, an inertial measurement unit, and an altitude sonar to provide relative position, velocity, and attitude information. A wall-following guidance rule is implemented to ensure that the vehicle explores maximum indoor area in a reasonable amount of time. A model reference adaptive control architecture is used to ensure stability and mitigation of uncertainties. The vehicle is intended to be Georgia Tech Aerial Robotic Team's entry for the 2011 International Aerial Robotics Competition (IARC) Symposium on Indoor Flight Issues

Georgia Tech Team Entry for the 2013 AUVSI International Aerial Robotics Competition

Presented at the Fifth International Aerial Robotics Competition (IARC) Symposium on Indoor Flight Issues, Grand Forks, ND, August, 201

Georgia Tech Team Entry for the 2012 AUVSI International Aerial Robotics Competition

Presented at the Third International Aerial Robotics Symposium (IASR), 2012.This paper describes the details of a Quadrotor Unmanned Aerial Vehicle capable of exploring cluttered indoor areas without relying on any external navigational aids. A Simultaneous Localization and Mapping (SLAM) algorithm is used to fuse information from a laser range sensor, an inertial measurement unit, and an altitude sonar to provide relative position, velocity, and attitude information. A wall avoidance and guidance system is implemented to ensure that the vehicle explores maximum indoor area. A model reference adaptive control architecture is used to ensure stability and mitigation of uncertainties. Finally, an object detection system is implemented to identify target objects for retrieval

Effect of ten-valent pneumococcal conjugate vaccine introduction on pneumococcal carriage in Fiji: results from four annual cross-sectional carriage surveys.

BACKGROUND: The indirect effects of pneumococcal conjugate vaccines (PCVs) are mediated through reductions in carriage of vaccine serotypes. Data on PCVs in Asia and the Pacific are scarce. Fiji introduced the ten-valent PCV (PCV10) in 2012, with a schedule consisting of three priming doses at 6, 10, and 14 weeks of age and no booster dose (3 + 0 schedule) without catch-up. We investigated the effects of PCV10 introduction using cross-sectional nasopharyngeal carriage surveys. METHODS: We did four annual carriage surveys (one pre-PCV10 and three post-PCV10) in the greater Suva area in Fiji, during 2012-15, of 5-8-week-old infants, 12-23-month-old children, 2-6-year-old children, and their caregivers (total of 8109 participants). Eligible participants were of appropriate age, had axillary temperature lower than 37°C, and had lived in the community for at least 3 consecutive months. We used purposive quota sampling to ensure a proper representation of the Fiji population. Pneumococci were detected by real-time quantitative PCR, and molecular serotyping was done with microarray. FINDINGS: 3 years after PCV10 introduction, vaccine-serotype carriage prevalence declined, with adjusted prevalences (2015 vs 2012) of 0·56 (95% CI 0·34-0·93) in 5-8-week-old infants, 0·34 (0·23-0·49) in 12-23-month-olds, 0·47 (0·34-0·66) in 2-6-year-olds, and 0·43 (0·13-1·42) in caregivers. Reductions in PCV10 serotype carriage were evident in both main ethnic groups in Fiji; however, carriage of non-PCV10 serotypes increased in Indigenous Fijian infants and children. Density of PCV10 serotypes and non-PCV10 serotypes was lower in PCV10-vaccinated children aged 12-23 months than in PCV10-unvaccinated children of the same age group (PCV10 serotypes -0·56 [95% CI -0·98 to -0·15], p=0·0077; non-PCV10 serotypes -0·29 [-0·57 to -0·02], p=0·0334). INTERPRETATION: Direct and indirect effects on pneumococcal carriage post-PCV10 are likely to result in reductions in pneumococcal disease, including in infants too young to be vaccinated. Serotype replacement in carriage in Fijian children, particularly Indigenous children, warrants further monitoring. Observed changes in pneumococcal density might be temporal rather than vaccine related. FUNDING: Department of Foreign Affairs and Trade of the Australian Government through the Fiji Health Sector Support Program; Victorian Government's Operational Infrastructure Support Program; Bill & Melinda Gates Foundation

Monocular vision-aided inertial navigation for unmanned aerial vehicles

The reliance of unmanned aerial vehicles (UAVs) on GPS and other external navigation aids has become a limiting factor for many missions. UAVs are now physically able to fly in many enclosed or obstructed environments, due to the shrinking size and weight of electronics and other systems. These environments, such as urban canyons or enclosed areas, often degrade or deny external signals. Furthermore, many of the most valuable potential missions for UAVs are in hostile or disaster areas, where navigation infrastructure could be damaged, denied, or actively used against the vehicle. It is clear that developing alternative, independent, navigation techniques will increase the operating envelope of UAVs and make them more useful. This thesis presents work in the development of reliable monocular vision-aided inertial navigation for UAVs. The work focuses on developing a stable and accurate navigation solution in a variety of realistic conditions. First, a vision-aided inertial navigation algorithm is developed which assumes uncorrelated feature and vehicle states. Flight test results on a 80 kg UAV are presented, which demonstrate that it is possible to bound the horizontal drift with vision aiding. Additionally, a novel implementation method is developed for integration with a variety of navigation systems. Finally, a vision-aided navigation algorithm is derived within a Bierman-Thornton factored extended Kalman Filter (BTEKF) framework, using fully correlated vehicle and feature states. This algorithm shows improved consistency and accuracy by 2 to 3 orders of magnitude over the previous implementation, both in simulation and flight testing. Flight test results of the BTEKF on large (80 kg) and small (600 g) vehicles show accurate navigation over numerous tests.Ph.D

A Monocular Vision-aided Inertial Navigation System with Improved Numerical Stability

Presented at the AIAA Guidance Navigation and Control Conference, Kissimmee, Florida, January 2015.This paper develops a monocular vision-aided inertial navigation system based on the factored extended Kalman filter (EKF) proposed by Bierman and Thornton. The simultaneous localization and mapping (SLAM) algorithm measurement update and propagation steps are formulated in terms of the factored covariance matrix P = UDUT, and a novel method for efficiently adding and removing features from the covariance factors is presented. The system is compared to the standard EKF formulation in navigation performance and computational requirements. The proposed method is shown to improve numerical stability with minimal impact on computational requirements. Flight test results are presented which demonstrate navigation performance with a controller in the loop