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NASA NTRS2010

Landmark Detection in Orbital Images Using Salience Histograms

NASA's planetary missions have collected, and continue to collect, massive volumes of orbital imagery. The volume is such that it is difficult to manually review all of the data and determine its significance. As a result, images are indexed and searchable by location and date but generally not by their content. A new automated method analyzes images and identifies "landmarks," or visually salient features such as gullies, craters, dust devil tracks, and the like. This technique uses a statistical measure of salience derived from information theory, so it is not associated with any specific landmark type. It identifies regions that are unusual or that stand out from their surroundings, so the resulting landmarks are context-sensitive areas that can be used to recognize the same area when it is encountered again. A machine learning classifier is used to identify the type of each discovered landmark. Using a specified window size, an intensity histogram is computed for each such window within the larger image (sliding the window across the image). Next, a salience map is computed that specifies, for each pixel, the salience of the window centered at that pixel. The salience map is thresholded to identify landmark contours (polygons) using the upper quartile of salience values. Descriptive attributes are extracted for each landmark polygon: size, perimeter, mean intensity, standard deviation of intensity, and shape features derived from an ellipse fit.

Wagstaff, Kiri L.↗

NASA NTRS2005

A Landmark Based Position Estimation for Pinpoint Landing on Mars

Real-time position estimation for a descent lander is a critical technological need for many of NASA's planned in situ missions including landing on a number of bodies at locations of greatest scientific interest and sample return. In particular, it enables the capability to land precisely and safely in a scientifically promising but hazardous site and is a key technology to be demonstrated by NASA in the next decade. The key challenge of pinpoint landing (PPL) is how to localize the lander by recognizing the landmarks (craters) in the landing area and match them positively to a preexisting landmark database while the spacecraft is descending. In this paper, a real-time landmark based position estimation technique for pinpoint landing is suggested. This system includes three crucial components: (1) real time landmark detection, (2) real-time landmark matching and (3) state (both position and velocity) estimation. We discuss the performance analysis of this system. Finally, we show that the suggested technology is able to deliver a spacecraft to less than 100 m from a pre-selected landing site on Mars.

Pinpoint landing↗

NASA NTRS1971

Experiment M412: Landmark contrast measurements

The objective was to measure the visual contrast of landmarks with the surroundings to determine the relative visibility of terrestrial landmarks from positions outside the atmosphere. Because of a malfunction of the photometer, no photometric data were obtained. A trial sighting run was performed in which a landmark on the western African coast was sighted, tracked through the nadir, and photographed. The telemetry record of the photograph was examined. Telemetry data were inconsistent with the known conditions of the landmark.

Manry, C. E.↗

NASA NTRS1975

Attitude and orbit estimation using stars and landmarks

An extended Kalman filter is used to process line-of-sight measurements to stars and known landmarks providing a statistical indication of performance in estimating spacecraft attitude, orbital ephemeris, and the bias drift of a set of three strapdown gyros. The landmark measurements were assumed to have been taken from the imagery of an Earth-observing multispectral scanner. It is shown that filtering of these noisy measurements results in highly accurate estimates of the above parameters. Results are given showing the sensitivity of performance to various system parameters such as star tracker accuracy, errors in the knowledge of landmark position, and number of stars and landmarks processed.

White, R. L.↗

NASA NTRS2003

Autonomous landmark based spacecraft navigation system

An autonomous landmark based spacecraft navigation scheme is presented. This new schme involves the following data processing steps: image selection and planning; landmark detection; preliminary image matching; crater matching; database management; and finally landmark based orbit determination.

autonomous↗

NASA NTRS1972

Visual orientation performances of desert ants (Cataglyphis bicolor) toward astromenotactic directions and horizon landmarks

Experimental data, on the visual orientation of desert ants toward astromenotactic courses and horizon landmarks involving the cooperation of different direction finding systems, are given. Attempts were made to: (1) determine if the ants choose a compromise direction between astromenotactic angles and the direction toward horizon landmarks when both angles compete with each other or whether they decide alternatively; (2) analyze adaptations of the visual system to the special demands of direction finding by astromenotactic orientation or pattern recognition; and (3) determine parameters of visual learning behavior. Results show separate orientation mechanisms are responsible for the orientation of the ant toward astromenotactic angles and horizon landmarks. If both systems compete with each other, the ants switch over from one system to the other and do not perform a compromise direction.

Wehner, R.↗

NASA NTRS1972

Landmark navigation rule, a new navigation device.

Two new methods of landmark navigation were recently presented. The landmarks are assumed to be within sight of the navigator but with unknown positions. Both methods require computations which are time consuming when a computer is not available. This correspondence presents the concept of a new navigation device called 'landmark navigation rule' which eliminates all the computation effort required in both new methods. The device is simple in construction, lightweight, and consumes no power.

Hung, J. C.↗

NASA NTRS1973

Landmark navigation and topographical mapping.

Proposed new navigational and mapping techniques could be of interest when using unmanned vehicles in the exploration of planets within the solar system. Recently developed techniques make use of landmarks whose coordinates are unknown but within sight of the surface vehicle. The techniques described in the present paper still make use of landmarks whose positions are unknown; however, they offer the added features of (1) travel and mapping beyond the original landmarks by discarding them and choosing new ones, (2) the determination of ranges relative to a selected range at the original starting point, (3) the determination of the direction back to the original starting point or any other previously travelled point, and (4) travel and mapping regardless of whether an angle reference is available.

Bennett, J. E.↗

NASA NTRS1979

Experimental and simulation study results for video landmark acquisition and tracking technology

A synopsis of related Earth observation technology is provided and includes surface-feature tracking, generic feature classification and landmark identification, and navigation by multicolor correlation. With the advent of the Space Shuttle era, the NASA role takes on new significance in that one can now conceive of dedicated Earth resources missions. Space Shuttle also provides a unique test bed for evaluating advanced sensor technology like that described in this report. As a result of this type of rationale, the FILE OSTA-1 Shuttle experiment, which grew out of the Video Landmark Acquisition and Tracking (VILAT) activity, was developed and is described in this report along with the relevant tradeoffs. In addition, a synopsis of FILE computer simulation activity is included. This synopsis relates to future required capabilities such as landmark registration, reacquisition, and tracking.

Schappell, R. T.↗

NASA NTRS1992

Magellan ephemeris improvement using synthetic aperture radar landmark measurements

A technique is described for measuring the positions of landmarks in multiple SAR images of the surface of Venus taken aboard the Magellan spacecraft. These measurements are then used to improve the spacecraft orbit estimate. The Venus-fixed coordinates of the landmarks are also estimated, as are the low-order coefficients of the gravitational field. Sample results are shown for five-orbit and 13-orbit data arcs using hundreds of landmark measurements. Reasonably good fits to the data are obtained for the short-arc solutions, while the data fits over long arcs are poorer, possibly due to higher-order uncertainties in the gravitational field. A comparison of post-fit orbit uncertainties shows that the SAR data significantly improves the orbit estimate.

Chodas, Paul W.↗

NASA NTRS1997

Neural Network Based Sensory Fusion for Landmark Detection

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

Kumbla, Kishan -K.↗

NASA NTRS2007

Measuring Image Navigation and Registration Performance at the 3-Sigma Level Using Platinum Quality Landmarks

Geostationary Operational Environmental Satellite (GOES) Image Navigation and Registration (INR) performance is specified at the 3- level, meaning that 99.7% of a collection of individual measurements must comply with specification thresholds. Landmarks are measured by the Replacement Product Monitor (RPM), part of the operational GOES ground system, to assess INR performance and to close the INR loop. The RPM automatically discriminates between valid and invalid measurements enabling it to run without human supervision. In general, this screening is reliable, but a small population of invalid measurements will be falsely identified as valid. Even a small population of invalid measurements can create problems when assessing performance at the 3-sigma level. This paper describes an additional layer of quality control whereby landmarks of the highest quality ("platinum") are identified by their self-consistency. The platinum screening criteria are not simple statistical outlier tests against sigma values in populations of INR errors. In-orbit INR performance metrics for GOES-12 and GOES-13 are presented using the platinum landmark methodology.

Carr, James L.↗

NASA NTRS2007

Mapped Landmark Algorithm for Precision Landing

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

Johnson, Andrew↗

NASA NTRS2022

Lunar Rover Localization Using Craters as Landmarks

Onboard localization capabilities for planetary rovers to date have used relative navigation, by integrating combinations of wheel odometry, visual odometry, and inertial measurements during each drive to track position relative to the start of each drive. At the end of each drive, a “ground-in-the-loop” (GITL) interaction is used to get a position update from human operators in a more global reference frame, such as a map frame defined by orbital reconnaissance imaging of a large region around the rover’s current position. For Mars rovers, this typically has involved downlinking imagery from the rover mast cameras and using interactive visualization tools on Earth to register such images to the orbital reconnaissance images. For safety purposes, rover mission operations typically specify “keep out zones”, which human operators recognize as being unsafe in the orbital images. Autonomous rover drives are limited in distance so that accumulated relative navigation error does not risk the possibility of the rover driving into a keep out zone. The allowable autonomous drive distance in this mode of operation depends on the distribution of keep out zones and the accuracy of relative navigation; in practice, drive limits of a few hundred meters between GITL cycles are to be expected. Several rover mission concepts have recently been studied that require much longer drives between GITL cycles, particularly for the Moon. This includes lunar rover mission concepts that involve (1) driving mostly in sunlight at low latitudes, (2) driving in permanently shadowed regions near the south pole, and (3) a mixture of day and night driving in mid-latitudes. These concepts include total traverse distance requirements of up to 1,800 km in 4 Earth years, with individual drives of several kilometers between stops for downlink. These concepts require greater autonomy to minimize GITL cycles to enable such large range; onboard global localization is a key element of such autonomy. Multiple techniques have been studied in the past for onboard rover global localization, including radio navigation aiding from an orbiter, recognizing horizon landmarks that are known in a regional elevation map, and correlating a local elevation map created onboard the rover with a regional elevation map. These techniques all have drawbacks, including requiring an expensive extra mission element (navigation orbiter), unavailability of sufficient regional elevation map data, or limited accuracy in resulting position estimates (e.g. a few hundred meters with horizon landmarks). For the Moon, the ubiquitous craters offer another possibility, which involves mapping craters from orbit, then recognizing crater landmarks with cameras and/or a lidar onboard the rover. This approach is applicable everywhere on the Moon, does not require high resolution stereo imaging from orbit as some other approaches do, and has potential to enable position knowledge with order of 10 m accuracy at all times. This paper will provide more detail on our technical approach to crater-based lunar rover localization and will present initial results on crater detection using 3-D point cloud data from onboard lidar or stereo cameras and using shading cues in monocular onboard imagery.

Ono, M.↗

NASA NTRS2002

Three dimensional landmark templates

Three-dimensional surface templates are being used to identify and locate landmarks on Mars and Phobos. They can be aligned both with images and the MOLA map to help tie these two data types together. The Martian templates form a control network of well-defined and easily identified landmarks.

landmarks Mars Phobos MOLA three-dimensional surfa↗

NASA NTRS2001

Automated landmark identification for spacecraft navigation

An integrated approach to surface relative optical landmark tracking for spacecraft is being developed. Landmarks are defined as full digital topography/albedo maps and are determined from previous imaging and navigation data. Initially, this technique will speed up ground based optical navigation. Ultimately, it will enable on-board trajectory determination during orbital and landing maneuvers.

landmark↗

NASA NTRS1971

A method for lunar roving vehicle position determination from three landmark observations with a sun compass

A simplified method is described for determining the position of the lunar roving vehicle on the lunar surface during Apollo 15. The method is based upon sun compass azimuth measurements of three lunar landmarks. The difference between the landmark azimuth and the sun azimuth is measured and the resulting data are voice relayed to the Mission Control Center for processing.

Blucker, T. J.↗

NASA NTRS1972

Comments on the figure of the moon from Apollo landmark tracking.

The selenographic positions of the observed lunar features are solved for, or estimated directly from, angular measurements made from the orbiting spacecraft (Apollo missions 8, 10, 11, 12, 14, and 15) to the landmark, using least-squares techniques. It appears that the radius values derived from the Apollo landmark data provide some proof of the existence of a displacement between the center of figure and center of mass of the moon along the earth-moon line. In addition, all three components of the estimated crater locations should be useful toward establishing a selenodetic reference system for interpreting or reducing earth-based observation data.

Wollenhaupt, W. R.↗