Homography-based depth recovery with descent images

In planetary landing exploration task, the images captured by the landing camera are nearly along optical axis which results in multi-resolution images of same terrain surface. Recovering the surface shape of landing terrain from descent imagery is of great value for lander to choose safe landing area. In this paper, a homography-based depth recovery method with descent images is addressed. At first, the parallax and scale change in descent images are analyzed. Second, the camera motion is optimized with SIFT features correspondence constraints. For dense depth recovery, a set of virtual parallel planes is assumed to slice the terrain and each plane induces a homography to warp back the second image to first image plane. Zero-normalized cross-correlation score is chosen to compute the correlation score and the correlation curve is smoothed by two Gaussian filters. The depth for each pixel is determined by the plane which has highest correlation value. At the end, some experiments are conducted, including different correlation computation, depth recovery with different terrain, and the error tests. The results show that the discussed method is feasible to recover the depth information overall.     

A stereo-vision system for support of planetary surface exploration

Abstract. In this paper, we present a system that was developed for the European Space Agency (ESA) for the support of planetary exploration. The system that is sent to the planetary surface consists of a rover and a lander. The lander contains a stereo head equipped with a pan-tilt mechanism. This vision system is used both for modeling the terrain and for localization of the rover. Both tasks are necessary for the navigation of the rover. Due to the stress that occurs during the flight, a recalibration of the stereo-vision system is required once it is deployed on the planet. Practical limitations make it unfeasible to use a known calibration pattern for this purpose; therefore, a new calibration procedure had to be developed that could work on images of the planetary environment. This automatic procedure recovers the relative orientation of the cameras and the pan and tilt axes, as well as the exterior orientation for all the images. The same images are subsequently used to reconstruct the 3-D structure of the terrain. For this purpose, a dense stereo-matching algorithm is used that (after rectification) computes a disparity map. Finally, all the disparity maps are merged into a single digital terrain model. In this paper, a simple and elegant procedure is proposed that achieves that goal. The fact that the same images can be used for both calibration and 3-D reconstruction is important, since, in general, the communication bandwidth is very limited. In addition to navigation and path planning, the 3-D model of the terrain is also used for virtual-reality simulations of the mission, wherein the model is texture mapped with the original images. The system has been implemented, and the first tests on the ESA planetary terrain testbed were successful.     

SLAM for autonomous planetary rovers with global localization

This paper describes a novel approach to simultaneous localization and mapping (SLAM) techniques applied to the autonomous planetary rover exploration scenario to reduce both the relative and absolute localization errors, using two well‐proven techniques: particle filters and scan matching. Continuous relative localization is improved by matching high‐resolution sensor scans to the online created local map. Additionally, to avoid issues with drifting localization, absolute localization is globally corrected at discrete times, according to predefined event criteria, by matching the current local map to the orbiter's global map. The resolutions of local and global maps can be appropriately chosen for computation and accuracy purposes. Further, the online generated local map, of the form of a structured elevation grid map, can also be used to evaluate the traversability of the surrounding environment and allow for continuous navigation. The objective of this study is to support long‐range low‐supervision planetary exploration. The implemented SLAM technique has been validated with a data set acquired during a field test campaign performed at the Teide Volcano on the island of Tenerife, representative of a Mars/Moon exploration scenario.     

Mars microrover navigation: Performance evaluation and enhancement

In 1996, NASA will launch the Mars Pathfinder spacecraft, which will carry an 11 kg rover to explore the immediate vicinity of the lander. To assess the capabilities of the rover, as well as to set priorities for future rover research, it is essential to evaluate the performance of its autonomous navigation system as a function of terrain characteristics. Unfortunately, very little of this kind of evaluation has been done, for either planetary rovers or terrestrial applications. To fill this gap, we have constructed a new microrover testbed consisting of the Rocky 3.2 vehicle and an indoor test arena with overhead cameras for automatic, real-time tracking of the true rover position and heading. We create Mars analog terrains in this arena by randomly distributing rocks according to an exponential model of Mars rock size frequency created from Viking lander imagery. To date, we have recorded detailed logs from over 85 navigation trials in this testbed. In this paper, we outline current plans for Mars exploration over the next decade, summarize the design of the lander and rover for the 1996 Pathfinder mission, and introduce a decomposition of rover navigation into four major functions: goal designation, rover localization, hazard detection, and path selection. We then describe the Pathfinder approach to each function, present results to date of evaluating the performance of each function, and outline our approach to enhancing performance for future missions. The results show key limitations in the quality of rover localization, the speed of hazard detection, and the ability of behavior control algorithms for path selection to negotiate the rock frequencies likely to be encountered on Mars. We believe that the facilities, methodologies, and to some extent the specific performance results presented here will provide valuable examples for efforts to evaluate robotic vehicle performance in other applications.     

The Mars exploration rovers descent image motion estimation system

Descent image motion estimation system is the first machine-vision system for estimating lander velocity during planetary descent. Composed of sensors and software, DIMES features a descent imager, a radar altimeter, an inertial-measurement unit, and an algorithm for combining sensor measurements to estimate horizontal velocity - the speed across the planet's surface the lander travels as it descends. Although the sensors are not novel technology, the algorithm and flight software that combines them are new. This algorithm combines radar, image, and inertial data in a novel way to create a low-cost, robust, and computationally efficient solution to the horizontal-velocity-estimation problem. This article describes the DIMES algorithm, its testing, and its performance during both Mars exploration rover landings.     

Mars Rover Autonomous Navigation

Autonomous navigation of a rover on Mars surface can improve very significantly the daily traverse, particularly when driving away from the lander, into unknown areas. The autonomous navigation process developed at CNES is based on stereo cameras perception, used to build a model of the environment and generate trajectories. Multiple perception merging with propagation of the locomotion and localization errors have been implemented. The algorithms developed for Mars exploration programs, the vision hardware, the validation tools, experimental platforms and results of evaluation are presented. Portability and the evaluation of computing resources for implementation on a Mars rover are also addressed. The results show that the implementation of autonomy requires only a very small amount of energy and computing time and that the rover capabilities are fully used, allowing a much longer daily traverse than what is enabled by purely ground-planned strategies.     

Mars Pathfinder Microrover

When the Mars Pathfinder (MPF) spacecraft lands on Mars, the Microrover Flight Experiment (MFEX) will be deployed and perform its mission to conduct technology experiments verifying the engineering design, to deploy an alpha proton x-ray spectrometer (APXS) to measure elemental properties of rocks and soil, and to image the MPF lander. In accomplishing this mission the MFEX rover must determine a safe path to goal locations traversing over a poorly known Martian surface. The rover does this mission with a capable mobile platform executing on-board autonomous functions of navigation and hazard avoidance. In this paper we describe the rover, its operational environment and the implementation of the on-board autonomous functions.     

Long‐range rover localization by matching LIDAR scans to orbital elevation maps

Current rover localization techniques such as visual odometry have proven to be very effective on short‐ to medium‐length traverses (e.g., up to a few kilometers). This paper deals with the problem of long‐range rover localization (e.g., 10 km and up) by developing an algorithm named MOGA (Multi‐frame Odometry‐compensated Global Alignment). This algorithm is designed to globally localize a rover by matching features detected from a three‐dimensional (3D) orbital elevation map to features from rover‐based, 3D LIDAR scans. The accuracy and efficiency of MOGA are enhanced with visual odometry and inclinometer/sun‐sensor orientation measurements. The methodology was tested with real data, including 37 LIDAR scans of terrain from a Mars–Moon analog site on Devon Island, Nunavut. When a scan contained a sufficient number of good topographic features, localization produced position errors of no more than 100 m, of which most were less than 50 m and some even as low as a few meters. Results were compared to and shown to outperform VIPER, a competing global localization algorithm that was given the same initial conditions as MOGA. On a 10‐km traverse, MOGA's localization estimates were shown to significantly outperform visual odometry estimates. This paper shows how the developed algorithm can be used to accurately and autonomously localize a rover over long‐range traverses. © 2010 Wiley Periodicals, Inc.     

Range‐dependent Terrain Mapping and Multipath Planning using Cylindrical Coordinates for a Planetary Exploration Rover

This paper presents terrain mapping and path‐planning techniques that are key issues for autonomous mobility of a planetary exploration rover. In this work, a LIDAR (light detection and ranging) sensor is used to obtain geometric information on the terrain. A point cloud of the terrain feature provided from the LIDAR sensor is usually converted to a digital elevation map. A sector‐shaped reference grid for the conversion process is proposed in this paper, resulting in an elevation map with cylindrical coordinates termed as C²DEM. This conversion approach achieves a range‐dependent resolution for the terrain mapping: a detailed terrain representation near the rover and a sparse representation far from the rover. The path planning utilizes a cost function composed of terrain inclination, terrain roughness, and path length indices, each of which is subject to a weighting factor. The multipath planning developed in this paper first explores possible sets of weighting factors and generates multiple candidate paths. The most feasible path is then determined by a comparative evaluation between the candidate paths. Field experiments with a rover prototype at a Lunar/Martian analog site were performed to confirm the feasibility of the proposed techniques, including the range‐dependent terrain mapping with C²DEM and the multipath‐planning method.     

Fast approximate clearance evaluation for rovers with articulated suspension systems

We present a light‐weight body‐terrain clearance evaluation algorithm for the automated path planning of NASA's Mars 2020 rover. Extraterrestrial path planning is challenging due to the combination of terrain roughness and severe limitation in computational resources. Path planning on cluttered and/or uneven terrains requires repeated safety checks on all the candidate paths at a small interval. Predicting the future rover state requires simulating the vehicle settling on the terrain, which involves an inverse‐kinematics problem with iterative nonlinear optimization under geometric constraints. However, such expensive computation is intractable for slow spacecraft computers, such as RAD750, which is used by the Curiosity Mars rover and upcoming Mars 2020 rover. We propose the approximate clearance evaluation (ACE) algorithm, which obtains conservative bounds on vehicle clearance, attitude, and suspension angles without iterative computation. It obtains those bounds by estimating the lowest and highest heights that each wheel may reach given the underlying terrain, and calculating the worst‐case vehicle configuration associated with those extreme wheel heights. The bounds are guaranteed to be conservative, hence ensuring vehicle safety during autonomous navigation. ACE is planned to be used as part of the new onboard path planner of the Mars 2020 rover. This paper describes the algorithm in detail and validates our claim of conservatism and fast computation through experiments.     

Visual Odometry for a Hopping Rover on an Asteroid Surface using Multiple Monocular Cameras

Visual odometry refers to the use of images to estimate the motion of a mobile robot. Real-time systems have already been demonstrated for terrestrial robotic vehicles, while a near real-time system has been successfully used on the Mars Exploration Rovers for planetary exploration. In this paper, we adapt this method to estimate the motion of a hopping rover on an asteroid surface. Due to the limited stereo depth resolution and the continuous rotational motion on a hopping rover, we propose to use a system of multiple monocular cameras. We describe how the scale of the scene observed by different cameras without overlapping views can be transferred between the cameras, allowing us to reconstruct a single continuous trajectory from multiple image sequences. We describe the implementation of our algorithm and its performance under simulation using rendered images.     

Seeker—Autonomous Long‐range Rover Navigation for Remote Exploration

Under the umbrella of the European Space Agency (ESA) StarTiger program, a rapid prototyping study called Seeker was initiated. A range of partners from space and nonspace sectors were brought together to develop a prototype Mars rover system capable of autonomously exploring several kilometers of highly representative Mars terrain over a three‐day period. This paper reports on our approach and the final field trials that took place in the Atacama Desert, Chile. Long‐range navigation and the associated remote rover field trials are a new departure for ESA, and this activity therefore represents a novel initiative in this area. The primary focus was to determine if current computer vision and artificial intelligence based software could enable such a capability on Mars, given the current limit of around 200 m per Martian day. The paper does not seek to introduce new theoretical techniques or compare various approaches, but it offers a unique perspective on their behavior in a highly representative environment. The final system autonomously navigated 5.05 km in highly representative terrain during one day. This work is part of a wider effort to achieve a step change in autonomous capability for future Mars/lunar exploration rover platforms.     

Finding the right pixel size

This paper discusses empirical and analytical rules to select a suitable grid resolution for output maps and based on the inherent properties of the input data. The choice of grid resolution was related with the cartographic and statistical concepts: scale, computer processing power, positional accuracy, size of delineations, inspection density, spatial autocorrelation structure and complexity of terrain. These were further related with the concepts from the general statistics and information theory such as Nyquist frequency concept from signal processing and equations to estimate the probability density function. Selection of grid resolution was demonstrated using four datasets: (1) GPS positioning data—the grid resolution was related to the area of circle described by the error radius, (2) map of agricultural plots—the grid resolution was related to the size of smallest and narrowest plots, (3) point dataset from soil mapping—the grid resolution was related to the inspection density, nugget variation and range of spatial autocorrelation and (4) contour map used for production of digital elevation model—the grid resolution was related with the spacing between the contour lines i.e. complexity of terrain. It was concluded that no ideal grid resolution exists, but rather a range of suitable resolutions. One should at least try to avoid using resolutions that do not comply with the effective scale or inherent properties of the input dataset. Three standard grid resolutions for output maps were finally recommended: (a) the coarsest legible grid resolution—this is the largest resolution that we should use in order to respect the scale of work and properties of a dataset; (b) the finest legible grid resolution—this is the smallest grid resolution that represents 95% of spatial objects or topography; and (c) recommended grid resolution—a compromise between the two. Objective procedures to derive the true optimal grid resolution that maximizes the predictive capabilities or information content of a map are further discussed. This methodology can now be integrated within a GIS package to help inexperienced users select a suitable grid resolution without doing extensive data preprocessing.     

Surface Maps via Adaptive Triangulations

We present a new method to compute continuous and bijective maps (surface homeomorphisms) between two or more genus-0 triangle meshes. In contrast to previous approaches, we decouple the resolution at which a map is represented from the resolution of the input meshes. We discretize maps via common triangulations that approximate the input meshes while remaining in bijective correspondence to them. Both the geometry and the connectivity of these triangulations are optimized with respect to a single objective function that simultaneously controls mapping distortion, triangulation quality, and approximation error. A discrete-continuous optimization algorithm performs both energy-based remeshing as well as global second-order optimization of vertex positions, parametrized via the sphere. With this, we combine the disciplines of compatible remeshing and surface map optimization in a unified formulation and make a contribution in both fields. While existing compatible remeshing algorithms often operate on a fixed pre-computed surface map, we can now globally update this correspondence during remeshing. On the other hand, bijective surface-to-surface map optimization previously required computing costly overlay meshes that are inherently tied to the input mesh resolution. We achieve significant complexity reduction by instead assessing distortion between the approximating triangulations. This new map representation is inherently more robust than previous overlay-based approaches, is less intricate to implement, and naturally supports mapping between more than two surfaces. Moreover, it enables adaptive multi-resolution schemes that, e.g., first align corresponding surface regions at coarse resolutions before refining the map where needed. We demonstrate significant speedups and increased flexibility over state-of-the art mapping algorithms at similar map quality, and also provide a reference implementation of the method.     

Horizon Map Capture

We present a method for computing horizon maps from captured images of a bumpy surface. 1Horizon maps encode surface self-shadowing effects, and can be used with bump or normals maps to realistically render surfaces with small height perturbations. The method does not rely on complete surface reconstruction, and requires only eight captured images as input. In this paper we discuss how shadow information is extrapolated from the eight captured images to compute the horizon map. Our implementation accounts for the noise and uncertainties in physically acquired data.     

Field testing of a rover guidance, navigation, and control architecture to support a ground-ice prospecting mission to Mars

This paper provides an overview of a rover guidance, navigation, and control (GN&C) architecture being developed to support a ground-ice prospecting mission to Mars. The main contribution of this paper is to detail an integrated field campaign that demonstrates the viability of the key rover GN&C techniques needed to carry out this mission. Tests were conducted on Devon Island in the Canadian High Arctic during the summer of 2009, wherein a large field robot was driven on real polygonal terrain (a landform of interest on Mars). Lessons learned and recommendations for future work are provided.     

Effect of spatial variation on areal evapotranspiration simulation in Haibei,Tibet plateau,China

Quantification of areal evapotranspiration from remote sensing data requires the determination of surface energy balance components with support of field observations. Much attention should be given to spatial resolution sensitivity to the physics of surface heterogeneity. Using the Priestley–Taylor model, we generated evapotranspiration maps at several spatial resolutions for a heterogeneous area at Haibei, and validated the evapotranspiration maps with the flux tower data. The results suggested that the mean values for all evapotranspiration maps were quite similar but their standard deviations decreased with the coarsening of spatial resolution. When the resolution transcended about 480 m, the standard deviations drastically decreased, indicating a loss of spatial structure information of the original resolution evapotranspiration map. The absolute values of relative errors of the points for evapotranspiration maps showed a fluctuant trend as spatial resolution of input parameter data layers coarsening, and the absolute value of relative errors reached minimum when pixel size of map matched up to measuring scale of eddy covariance system. Finally, based on the analyses of the semi‐variogram of the original resolution evapotranspiration map and the shapes of spatial autocorrelation indices of Moran and Geary for evapotranspiration maps at different resolutions, an appropriate resolution was suggested for the areal evapotranspiration simulation in this study area.     

Planetary Rover Developments Supporting Mars Exploration, Sample Return and Future Human-Robotic Colonization

We overview our recent research on planetary mobility. Products of this effort include the Field Integrated Design & Operations rover (FIDO), Sample Return Rover (SRR), reconfigurable rover units that function as an All Terrain Explorer (ATE), and a multi-Robot Work Crew of closely cooperating rovers (RWC). FIDO rover is an advanced technology prototype; its design and field testing support NASA's development of long range, in situ Mars surface science missions. Complementing this, SRR implements autonomous visual recognition, navigation, rendezvous, and manipulation functions enabling small object pick-up, handling, and precision terminal docking to a Mars ascent vehicle for future Mars Sample Return. ATE implements on-board reconfiguration of rover geometry and control for adaptive response to adverse and changing terrain, e.g., traversal of steep, sandy slopes. RWC implements coordinated control of two rovers under closed loop kinematics and force constraints, e.g., transport of large payloads, as would occur in robotic colonies at future Mars outposts. RWC is based in a new extensible architecture for decentralized control of, and collective state estimation by multiple heterogeneous robotic platforms—CAMPOUT; we overview the key architectural features. We have conducted experiments with all these new rover system concepts over variable natural terrain. For each of the above developments, we summarize our approach, some of our key experimental results to date, and our future directions of planned development.     

Theory and experiments in SmartNav rover navigation

This paper describes theoretical and experimental results using the SmartNav rule-free fuzzy rover navigation system. SmartNav divides the terrain perceived by the rover into a number of circular sectors, and evaluates each sector using goal and safety preference factors to differentiate between preferred and unpreferred terrain sectors. The goal-preference factor is used to make sector evaluation based on the sector orientation relative to the designated goal position. The safety-preference factors are used to make sector evaluations on the basis of the sector local and regional terrain hazards. Three methods are developed to blend the three sector evaluations in order to find the effective preference factor for each sector. Two sector selection methods are then described in which the sector preference factors are used to find the heading command for the rover. The rover speed command is also computed based on the goal distance and safety-preference factor of the chosen sector. The above navigation steps are continuously repeated throughout the rover motion. Experimental results are presented to demonstrate the navigational capabilities of SmartNav using a commercial Pioneer 2AT rover traversing a simulated Martian terrain at the JPL Mini Mars Yard.

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Multi-resolution terrain rendering with GPU tessellation

GPU tessellation is very efficient and is reshaping the terrain-rendering paradigm. We present a novel terrain-rendering algorithm based on GPU tessellation. The planar domain of the terrain is partitioned into a set of tiles, and a coarse-grained quadtree is constructed for each tile using a screen-space error metric. Then, each node of the quadtree is input to the GPU pipeline together with its own tessellation factors. The nodes are tessellated and the vertices of the tessellated mesh are displaced by filtering the displacement maps. The multi-resolution scheme is designed to optimize the use of GPU tessellation. Further, it accepts not only height maps but also geometry images, which displace more vertices toward the higher curvature feature parts of the terrain surface such that the surface detail can be well reconstructed with a small number of vertices. The efficiency of the proposed method is proven through experiments on large terrain models. When the screen-space error threshold is set to a pixel, a terrain surface tessellated into 8.5 M triangles is rendered at 110 fps on commodity PCs.