Vision-Aided Navigation for GPS-Denied Environments Using Landmark Feature Identification

In recent years, unmanned autonomous vehicles have been used in diverse applications because of their multifaceted capabilities. In most cases, the navigation systems for these vehicles are dependent on Global Positioning System (GPS) technology. Many applications of interest, however, entail operations in environments in which GPS is intermittent or completely denied. These applications include operations in complex urban or indoor environments as well as missions in adversarial environments where GPS might be denied using jamming technology. This thesis investigate the development of vision-aided navigation algorithms that utilize processed images from a monocular camera as an alternative to GPS. The vision-aided navigation approach explored in this thesis entails defining a set of inertial landmarks, the locations of which are known within the environment, and employing image processing algorithms to detect these landmarks in image frames collected from an onboard monocular camera. These vision-based landmark measurements effectively serve as surrogate GPS measurements that can be incorporated into a navigation filter. Several image processing algorithms were considered for landmark detection and this thesis focuses in particular on two approaches: the continuous adaptive mean shift (CAMSHIFT) algorithm and the adaptable compressive (ADCOM) tracking algorithm. These algorithms are discussed in detail and applied for the detection and tracking of landmarks in monocular camera images. Navigation filters are then designed that employ sensor fusion of accelerometer and rate gyro data from an inertial measurement unit (IMU) with vision-based measurements of the centroids of one or more landmarks in the scene. These filters are tested in simulated navigation scenarios subject to varying levels of sensor and measurement noise and varying number of landmarks. Finally, conclusions and recommendations are provided regarding the implementation of this vision-aided navigation approach for autonomous vehicle navigation systems

Automatic Life Saving Device in Commercial Aircrafts using Feedback Control System

Several safety devices have filled in the vacuous spaces in commercial airplanes which once did not possess such sophisticated mechanisms. Commercial airplanes have copious amount of instruments and electrical circuits to provide a proper control system inside the plane. A noteworthy invention in the early 80â??s is the oxygen masks provided for every passenger during a plane crash or if the airplane is subjected to climatic disturbances while travelling a passenger manually uses the oxygen masks. The oxygen control system in the airplanes has proved very effective in providing an overall safety to the passengers. But the technique given below is far more advanced than the present scenario. A person suffering from a breathing ailment is succumbed to variations in the carbon dioxide levels. Thereby this CO2 is measured and using a feedback control loop, quick actions can be taken in order to provide quick aid to the ailing patient. These are completely automatic and hence it is advanced than the manual oxygen control system presently used in all commercial aircrafts. At the end of the day saving a life is what a humanistic approach is all about

Vision-Aided Navigation for a Free-Flying Unmanned Robotic System to Support Interplanetary Bodies Prospecting and Characterization Missions

This paper investigates vision-aided navigation strategies for an autonomous free-flying robotic vehicle designed to explore interplanetary bodies, such as moons or asteroids, for the purposes of In Situ Resource Utilization (ISRU). ISRU has the potential to facilitate planetary exploration by drawing needed resources, such as water, from the local environment. The realization of ISRU requires the development of advanced unmanned space systems integrated with sample-capture devices and guidance, navigation, and control systems capable of supporting autonomous exploration of challenging environments such as craters and lava tubes. Navigation on interplanetary bodies is challenging due to the unavailability of traditional navigation sesnors such as GPS and magnetometers. This paper focuses on the use of one or more vision sensors to augment an onboard inertial measurement unit, which is composed of accelerometers and rate gyros, in order to provide vision-aided navigation solutions for the free-flyer robotic system. In this study, a vision-aided navigation strategy is considered that entails using object detection and tracking algorithms to identify known landmarks in the scene, which provides information that can be used to estimate the position of the vehicle within the environment. Vision-aided navigation filters are developed for a stereo implementation of landmark detection and tracking, and the algorithms are implemented on video obtained from flights of a quadrotor UAV at the Hazard Field at the NASA Kennedy Space Center