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At least 127 records · Page 7

4DoF Drift Free Navigation Using Inertial Cues and Optical Flow

In this paper, we describe a novel approach in fusing optical flow with inertial cues (3D acceleration and 3D angular velocities) in order to navigate a Micro Aerial Vehicle (MAV) drift free in 4DoF and metric velocity. Our approach only requires two consecutive images with a minimum of three feature matches. It does not require any (point) map nor any type of feature history. Thus it is an inherently failsafe approach that is immune to map and feature-track failures. With these minimal requirements we show in real experiments that the system is able to navigate drift free in all angles including yaw, in one metric position axis, and in 3D metric velocity. Furthermore, it is a power-on-and-go system able to online self-calibrate the inertial biases, the visual scale and the full 6DoF extrinsic transformation parameters between camera and IMU.

reconnissance↗

Inertially-aided, all-weather landing systems for C/TOL

Ways to improve significantly all-weather landing systems technology for conventional take-off and landing vehicles, primarily, the large commercial jets, were studied. It was concluded that there is a great deal to be gained by extensive use of inertial navigation system derived information, primarily, the translational information inherent in an inertial navigator, for improving all-weather landing system performance.

Pawlak, R. J.↗

Integrated Displays For Helicopter Pilots

Report evaluates three similar video displays for guidance of helicopter pilots in low-level flight at night in adverse weather. Computer produces guidance information for pilot by integrating data from terrain-following radar, forward-looking infrared (FLIR) imagery, and data from such autonomous navigation instruments as inertial navigation systems and Doppler radar. FLIR imagery, information on status of helicopter, and command symbols incorporated in one head-down display.

Swenson, Harry N.↗

Failure detection and isolation analysis of a redundant strapdown inertial measurement unit

The objective of this study was to define and develop techniques for failure detection and isolation (FDI) algorithms for a dual fail/operational redundant strapdown inertial navigation system are defined and developed. The FDI techniques chosen include provisions for hard and soft failure detection in the context of flight control and navigation. Analyses were done to determine error detection and switching levels for the inertial navigation system, which is intended for a conventional takeoff or landing (CTOL) operating environment. In addition, investigations of false alarms and missed alarms were included for the FDI techniques developed, along with the analyses of filters to be used in conjunction with FDI processing. Two specific FDI algorithms were compared: the generalized likelihood test and the edge vector test. A deterministic digital computer simulation was used to compare and evaluate the algorithms and FDI systems.

Motyka, P.↗

Inertial navigation/calibration/precise time and frequency capabilities

The Aerospace Guidance and Metrology Center was conceived in 1959 to be the US Air Force Inertial Navigation and Metrology Center. This paper will show the mission capabilities of the Inertial Navigation Maintenance Center and the Air Force Measurement and Standards Laboratory. Highlighted will be the precise time and frequency program developed by AGMC to support Air Force precise time and frequency requirements worldwide. A description of the past, present, and future precise time and frequency activities will be presented.

Galloway, L. M.↗

Automated Point Cloud Correspondence Detection for Underwater Mapping Using AUVs

An algorithm for automating correspondence detection between point clouds composed of multibeam sonar data is presented. This allows accurate initialization for point cloud alignment techniques even in cases where accurate inertial navigation is not available, such as iceberg profiling or vehicles with low-grade inertial navigation systems. Techniques from computer vision literature are used to extract, label, and match keypoints between "pseudo-images" generated from these point clouds. Image matches are refined using RANSAC and information about the vehicle trajectory. The resulting correspondences can be used to initialize an iterative closest point (ICP) registration algorithm to estimate accumulated navigation error and aid in the creation of accurate, self-consistent maps. The results presented use multibeam sonar data obtained from multiple overlapping passes of an underwater canyon in Monterey Bay, California. Using strict matching criteria, the method detects 23 between-swath correspondence events in a set of 155 pseudo-images with zero false positives. Using less conservative matching criteria doubles the number of matches but introduces several false positive matches as well. Heuristics based on known vehicle trajectory information are used to eliminate these.

Sonar↗

Autonomous reconfigurable GPS/INS navigation and pointing system for rendezvous and docking

The briefing describes work using the Global Positioning System to determine position of spacecraft and the development of computer tools to utilize these position determinations to enable autonomous rendezvous. Using GPS data in conjunction with Inertial Navigation Systems (INS) provides the capability for absolute spacecraft navigation, navigation of one spacecraft relative to another, and attitude determination. Some results presented are based on limited observations, though simulation results are documented. A GPS/INS navigation flight experiment could provide a platform for evaluating approaches for autonomous operation and reconfigurability of the navigation and attitude determination subsystem for future space vehicles. Current emphasis is on the development and demonstration of an Onboard Mission Manager (OMM) and a Multi-Mode Navigation Kalman filter. Sensor data will be handed over to the OMM, which will determine the appropriate response and generate commands for the Kalman filter to use to reconfigure itself. Global Positioning System measurements and INS data will be processed in the integrated navigation filter and used to compute errors in position, velocity, and attitude. Inertial Navigation Systems instrument errors (biases, scale factors, etc.) also can be estimated. The OMM then will use a knowledge base to determine appropriate system response. The GPS is good for missions that have attitude pointing accuracy requirements within the 100 to 200 arcsecond range.

Upadhyay, Triveni M.↗

Precision Landing and Hazard Avoidance Doman

The Precision Landing and Hazard Avoidance (PL&HA) domain addresses the development, integration, testing, and spaceflight infusion of sensing, processing, and GN&C functions critical to the success and safety of future human and robotic exploration missions. PL&HA sensors also have applications to other mission events, such as rendezvous and docking. Autonomous PL&HA builds upon the core GN&C capabilities developed to enable soft, controlled landings on the Moon, Mars, and other solar system bodies. Through the addition of a Terrain Relative Navigation (TRN) function, precision landing within tens of meters of a map-based target is possible. The addition of a 3-D terrain mapping lidar sensor improves the probability of a safe landing via autonomous, real-time Hazard Detection and Avoidance (HDA). PL&HA significantly improves the probability of mission success and enhances access to sites of scientific interest located in challenging terrain. PL&HA can also utilize external navigation aids, such as navigation satellites and surface beacons. Advanced Lidar Sensors High precision ranging, velocimetry, and 3-D terrain mapping Terrain Relative Navigation (TRN) TRN compares onboard reconnaissance data with real-time terrain imaging data to update the S/C position estimate Hazard Detection and Avoidance (HDA) Generates a high-resolution, 3-D terrain map in real-time during the approach trajectory to identify safe landing targets Inertial Navigation During Terminal Descent High precision surface relative sensors enable accurate inertial navigation during terminal descent and a tightly controlled touchdown within meters of the selected safe landing target.

Robertson, Edward A.↗

LiDAR-Inertial Based Navigation and Mapping for Precision Landing

Future lander missions will travel to ambitious, scientifically interesting locations near rough and dangerous terrain. They will need to operate with limited prior information about the terrain, and under varying lighting conditions. Landing safely and precisely in the face of these challenges is difficult for existing vision-based landing systems, which require detailed orbital reconnaissance, a priori hazard maps, and impose time-of-day restrictions on landing to ensure similar lighting conditions in orbital and descent imagery. Advanced 3D imaging LiDAR systems currently under development, and originally intended for single-scan hazard detection, have the potential to be operated continuously from altitudes of up to 5 km. Used together with existing inertial measurement units (IMUs), these sensors open a path-to-flight for a full navigation and mapping system, which could replace or augment a traditional landing sensor suite. A landing system based around these sensors can perform accurate altimetry, map-relative localization (MRL), LiDAR-inertial odometry, and map refinement in an illumination-insensitive manner, over unknown or partially known terrain. This paper outlines preliminary work on a LiDAR-inertial landing system that: estimates the spacecraft trajectory during entry, descent, and landing (EDL); and maps the topography of the terrain below, for future use in hazard detection and avoidance. An incremental, factor graph based, smoothing approach is used to solve for the maximum a posteriori trajectory of spacecraft states. Integrated IMU measurements and features tracked in adjacent range and intensity images are used to estimate motion (LiDAR-inertial odometry). LiDAR scans are binned into motion-corrected digital elevation models (DEMs), which are matched to an existing orbital topographic map to provide absolute position information (MRL). The estimated trajectory is then used to project the LiDAR scans into the map frame, creating a variable-resolution quadtree topographic map suitable for hazard detection and avoidance. Existing topographic maps from throughout the solar system (i.e., Earth, the Moon, Mars, Ceres, Vesta, Europa, Enceladus, and Eros) are upsampled for use in EDL simulations. The Mars 2020 Lander Vision System Simulator (LVSS) is extended to simulate LiDAR-inertial data for realistic EDL trajectories. Results of the algorithm operating on the simulated data are presented. Estimated spacecraft trajectory and refined map are compared to ground truth to assess estimation accuracy.

Katake, Anup↗

Simultaneous dual-band radar development

Efforts to design and construct an airborne imaging radar operating simultaneously at L band and X band with an all-inertial navigation system in order to form a dual-band radar system are described. The areas of development include duplex transmitters, receivers, and recorders, a control module, motion compensation for both bands, and adaptation of a commercial inertial navigation system. Installation of the system in the aircraft and flight tests are described. Circuit diagrams, performance figures, and some radar images are presented.

Liskow, C. L.↗

Mapping of sea ice and measurement of its drift using aircraft synthetic aperture radar images

Side-looking radar images of Arctic sea ice were obtained as part of the Arctic Ice Dynamics Joint Experiment. Repetitive coverages of a test site in the Arctic were used to measure sea ice drift, employing single images and blocks of overlapping radar image strips; the images were used in conjunction with data from the aircraft inertial navigation and altimeter. Also, independently measured, accurate positions of a number of ground control points were available. Initial tests of the method were carried out with repeated coverages of a land area on the Alaska coast (Prudhoe). Absolute accuracies achieved were essentially limited by the accuracy of the inertial navigation data. Errors of drift measurements were found to be about + or - 2.5 km. Relative accuracy is higher; its limits are set by the radar image geometry and the definition of identical features in sequential images. The drift of adjacent ice features with respect to one another could be determined with errors of less than + or - 0.2 km.

Leberl, F.↗