A Window in the Future of Planetary Surface Navigation

The presentation focuses on surface navigation and mapping challenges in planetary environments including Lunar and Martian surface. Imagery from precursor orbital missions are processed to provide a medium resolution, large coverage 2D and 3D maps used by the science and navigation teams. During the surface mission these mapping products together with the images captured from the on-board camera systems are used in rover localization and navigation

Challenges in Planetary Mapping and Surface Navigation

The presentation focuses on surface navigation and mapping challenges in planetary environments including Lunar and Martian surface. Imagery from precursor orbital missions are processed to provide a medium resolution, large coverage 2D and 3D maps used by the science and navigation teams. During the surface mission these mapping products together with the images captured from the on-board camera systems are used in rover localization and navigation

Safeguarding a Lunar Rover with Wald's Sequential Probability Ratio Test

The virtual bumper is a safeguarding mechanism for autonomous and remotely operated robots. In this paper we take a new approach to the virtual bumper system by using an old statistical test. By using a modified version of Wald's sequential probability ratio test we demonstrate that we can reduce the number of false positive reported by the virtual bumper, thereby saving valuable mission time. We use the concept of sequential probability ratio to control vehicle speed in the presence of possible obstacles in order to increase certainty about whether or not obstacles are present. Our new algorithm reduces the chances of collision by approximately 98 relative to traditional virtual bumper safeguarding without speed control

Lunar Terrain and Albedo Reconstruction from Apollo Imagery

Generating accurate three dimensional planetary models and albedo maps is becoming increasingly more important as NASA plans more robotics missions to the Moon in the coming years. This paper describes a novel approach for separation of topography and albedo maps from orbital Lunar images. Our method uses an optimal Bayesian correlator to refine the stereo disparity map and generate a set of accurate digital elevation models (DEM). The albedo maps are obtained using a multi-image formation model that relies on the derived DEMs and the Lunar- Lambert reflectance model. The method is demonstrated on a set of high resolution scanned images from the Apollo era missions

Photometric Lunar Surface Reconstruction

Accurate photometric reconstruction of the Lunar surface is important in the context of upcoming NASA robotic missions to the Moon and in giving a more accurate understanding of the Lunar soil composition. This paper describes a novel approach for joint estimation of Lunar albedo, camera exposure time, and photometric parameters that utilizes an accurate Lunar-Lambertian reflectance model and previously derived Lunar topography of the area visualized during the Apollo missions. The method introduced here is used in creating the largest Lunar albedo map (16% of the Lunar surface) at the resolution of 10 meters/pixel

Structured Light-Based Hazard Detection For Planetary Surface Navigation

This paper describes a structured light-based sensor for hazard avoidance in planetary environments. The system presented here can also be used in terrestrial applications constrained by reduced onboard power and computational complexity and low illumination conditions. The sensor is on a calibrated camera and laser dot projector system. The onboard hazard avoidance system determines the position of the projected dots in the image and through a triangulation process detects potential hazards. The paper presents the design parameters for this sensor and describes the image based solution for hazard avoidance. The system presented here was tested extensively in day and night conditions in Lunar analogue environments. The current system achieves over 97 detection rate with 1.7 false alarms over 2000 images

Planetary Rover Localization Within Orbital Maps

This paper introduces an advanced rover localization system suitable for autonomous planetary exploration in the absence of Global Positioning System (GPS) infrastructure. Given an existing terrain map (image and elevation) obtained from satellite imagery and the images provided by the rover stereo camera system, the proposed method determines the best rover location through visual odometry, 3D terrain and hori- zon matching. The system is tested on data retrieved from a 3 km traverse of the Basalt Hills quarry in California where the GPS track is used as ground truth. Experimental results show the system presented here reduces by over 60 the localization error obtained by wheel odometry

Estimating Nuisance Parameters in Inverse Problems

Many inverse problems include nuisance parameters which, while not of direct interest, are required to recover primary parameters. Structure present in these problems allows efficient optimization strategies - a well known example is variable projection, where nonlinear least squares problems which are linear in some parameters can be very efficiently optimized. In this paper, we extend the idea of projecting out a subset over the variables to a broad class of maximum likelihood (ML) and maximum a posteriori likelihood (MAP) problems with nuisance parameters, such as variance or degrees of freedom. As a result, we are able to incorporate nuisance parameter estimation into large-scale constrained and unconstrained inverse problem formulations. We apply the approach to a variety of problems, including estimation of unknown variance parameters in the Gaussian model, degree of freedom (d.o.f.) parameter estimation in the context of robust inverse problems, automatic calibration, and optimal experimental design. Using numerical examples, we demonstrate improvement in recovery of primary parameters for several large- scale inverse problems. The proposed approach is compatible with a wide variety of algorithms and formulations, and its implementation requires only minor modifications to existing algorithms.Comment: 16 pages, 5 figure