Mars exploration

While some of the questions about Mars has been answered after about 40 years of exploration, many still remain. This paper looks back at what we have learned so far about Mars and then looks ahead at the missions planned, technologies needed, and further science clues sought through either robotic or human exploration.     

Wide-baseline stereo vision for terrain mapping

Terrain mapping is important for mobile robots to perform localization and navigation. Stereo vision has been used extensively for this purpose in outdoor mapping tasks. However, conventional stereo does not scale well to distant terrain. This paper examines the use of wide-baseline stereo vision in the context of a mobile robot for terrain mapping, and we are particularly interested in the application of this technique to terrain mapping for Mars exploration. In wide-baseline stereo, the images are not captured simultaneously by two cameras, but by a single camera at different positions. The larger baseline allows more accurate depth estimation of distant terrain, but the robot motion between camera positions introduces two new problems. One issue is that the robot estimates the relative positions of the camera at the two locations imprecisely, unlike the precise calibration that is performed in conventional stereo. Furthermore, the wide-baseline results in a larger change in viewpoint than in conventional stereo. Thus, the images are less similar and this makes the stereo matching process more difficult. Our methodology addresses these issues using robust motion estimation and feature matching. We give results using real images of terrain on Earth and Mars and discuss the successes and failures of the technique.     

Vibration-based terrain classification for planetary exploration rovers

Safe, autonomous mobility in rough terrain is an important requirement for planetary exploration rovers. Knowledge of local terrain properties is critical to ensure a rover's safety on slopes and uneven surfaces. Visual features are often used to classify terrain; however, vision can be sensitive to lighting variations and other effects. This paper presents a method to classify terrain based on vibrations induced in the rover structure by wheel-terrain interaction during driving. This sensing mode is robust to lighting variations. Vibrations are measured using an accelerometer mounted on the rover structure. The classifier is trained using labeled vibration data during an offline learning phase. Linear discriminant analysis is used for online identification of terrain classes, such as sand, gravel, or clay. This approach has been experimentally validated on a laboratory testbed and on a four-wheeled rover in outdoor conditions.     

ASTER ratio indices for supraglacial terrain mapping

Supraglacial terrain, such as that found in the Himalayas, is typically composed of snow, ice, ice‐mixed‐debris (IMD) and debris. This letter presents a methodology for systematic discrimination and mapping of these supraglacial cover types using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. The Normalized Difference Snow Index (NDSI) has been used previously for discrimination of snow/ice‐bearing zones versus debris. Two new indices, the Normalized Difference Glacier Index (NDGI) and the Normalized Difference Snow Ice Index (NDSII), are presented. The combination of all three indices allows discrimination of snow, ice and IMD in a systematic manner.     

Mars exploration rover mobility development

The Mars Exploration Rover (MER) Project was launched in mid-2000 to land two mobile exploration platforms at different science targets on the red planet. The centerpiece of each mission is the rover and its scientific payload. Spirit and Opportunity are identical vehicles, and each carries the same science payload and engineering subsystems. NASA's current Mars program is once again focused on missions to the Martian surface to answer fundamental questions of the extent Mars ever supported a liquid water environment on its surface, and hence the planet's ability to have sustained life.     

A GPU persistent grid mapping for terrain rendering

In this paper we present persistent grid mapping (PGM), a novel framework for interactive view-dependent terrain rendering. Our algorithm is geared toward high utilization of modern GPUs, and takes advantage of ray tracing and mesh rendering. The algorithm maintains multiple levels of the elevation and color maps to achieve a faithful sampling of the viewed region. The rendered mesh ensures the absence of cracks and degenerate triangles that may cause the appearance of visual artifacts. In addition, an external texture memory support is provided to enable the rendering of terrains that exceed the size of texture memory. Our experimental results show that the PGM algorithm provides high quality images at steady frame rates. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

The Mars exploration plans of ESA

In the framework of its Aurora Exploration Program, the European Space Agency (ESA) has initiated the ExoMars Project. Aside from searching for traces of life at and near the Martian surface, ExoMars aims to characterize the Martian geochemistry and water distribution at various locations, improve the knowledge of the Mars environment and geophysics, and identify possible hazards for future missions. Beyond the ExoMars Project, there is a strong scientific and technical interest in Europe to participate in an international Mars Sample Return (MSR) mission. ESA's overall approach to MSR includes a combination of system studies, technology development work, and the identification of capability development approaches including the consideration of demonstration missions. In the longer term, the approach intends to allow the strategic down-selection of specific areas in which Europe can play a strategic role in the eventual MSR mission.     

Visual exploration of production data using small multiples design with non-uniform color mapping

Visual data mining may overcome some of the flexibility problem often suffered by computer-centered data mining approaches. This can happen because human beings are introduced to the information discovery loop to take advantage of their natural strength in creative thinking and rapid visual pattern recognition to discover information not defined a priori and to perform approximated reasoning that computer algorithms are hard to do. This paper presents a novel visual exploration approach for mining abstract, multi-dimensional data stored in tables in a relational database. The visual image is constructed by converting each table into a visualization unit called a table graph and then assembling these table graphs together to form a small multiples design. Different types of non-uniform color mappings to render this small multiples design could be automatically generated by minimizing the weight differences of colors in the visual image. These non-uniform color mappings are designed in such a way that the adjacent glyphs in a table graph that have near underlying values will be assigned with the same color. As such, visual patterns not able to see under the traditional uniform color mapping could be revealed. This enables the users to examine the input tables from different perspectives. The proposed flexible visualization method has been applied to generate visual images from which the users could quickly and easily compare the machine idle cost performances of alternative master production plans.     

A novel filter for terrain mapping with laser rangefinders

This paper introduces a novel filter for terrain mapping with a two-dimensional laser rangefinder. The filter, called the certainty-assisted spatial (CAS) filter, uses the physical constraints on motion continuity and spatial continuity to identify corrupted pixels and missing data in an elevation map. The filter removes the corrupted pixels, fills in the missing data, and leaves the uncorrupted pixels intact so as to preserve the details of a terrain map. Our extensive indoor and outdoor mapping experiments show the CAS filter's superior performance in erroneous data reduction and map detail preservation over conventional filters.     

Visual odometry on the Mars exploration rovers - a tool to ensure accurate driving and science imaging

In this paper, visual odometry is presented as an approach to position estimation to find features in a stereo image pair and track them from one frame to the next. Visual odometry has been a highly effective tool for maintaining vehicle safety while driving near obstacles on slopes, achieving difficult drive approaches in fewer sols, and ensuring accurate science imaging. Although it requires active pointing by human drivers in feature-poor terrain, the improved position knowledge enables more autonomous capability and better science return during planetary operations.     

Progress towards robotic exploration of extreme terrain

A high degree of mobility, reliability, and efficiency are needed for autonomous exploration of extreme terrain. These requirements have guided the development of the Ambler, a six-legged robot designed for planetary exploration. To address issues of efficiency and mobility, the Ambler is configured with a stacked arrangement of orthogonal legs and exhibits a unique circulating gait, where trailing legs recover directly from rear to front. The Ambler is designed to stably traverse a 30 degree slope while crossing meter sized features. The same three principles have provided many constraints on the design of a software system that autonomously navigates the Ambler through natural terrain using 3-D perception and a combined deliberative/reactive architecture. The software system has required research advances in real-time control, perception of rugged terrain, motion planning, task-level control, and system integration. This paper presents many of the factors that influenced the design of the Ambler and its software system. In particular, important assumptions regarding the mechanism, perception, planning, and control are presented and evaluated in light of experimental and theoretical research of this project.     

Simplified radar mapping equations for terrain correction of space-borne SAR images

Correction of a space-borne Synthetic Aperture Radar (SAR) image for the effects of terrain distortion requires the use of mapping equations that relate the coordinates of a scatterer in three dimensions to its position in the twodimensional image. These mapping equations are complicated since they take into account the curved geometry of the Earth's surface, and since they must be evaluated of the order of 10 to 100 million times in the course of correcting a typical SAR image, the complexity is a disadvantage. In this paper we derive two approximations, one quadratic and one linear, to the mapping equation, and evaluate their performance relative to the observational parameters of a variety of space-borne SAR systems and the range of topographic variation present in the scene. We show that the quadratic approximation is sufficiently accurate in virtually all circumstances likely to be encountered. In most cases the linear approximation is also valid, although it is unsuitable where the topographic variation is large and the near-swath incidence angle is small.     

Planning exploration strategies for simultaneous localization and mapping

In this paper, we present techniques that allow one or multiple mobile robots to efficiently explore and model their environment. While much existing research in the area of Simultaneous Localization and Mapping (SLAM) focuses on issues related to uncertainty in sensor data, our work focuses on the problem of planning optimal exploration strategies. We develop a utility function that measures the quality of proposed sensing locations, give a randomized algorithm for selecting an optimal next sensing location, and provide methods for extracting features from sensor data and merging these into an incrementally constructed map.We also provide an efficient algorithm driven by our utility function. This algorithm is able to explore several steps ahead without incurring too high a computational cost. We have compared that exploration strategy with a totally greedy algorithm that optimizes our utility function with a one-step-look ahead.The planning algorithms which have been developed operate using simple but flexible models of the robot sensors and actuator abilities. Techniques that allow implementation of these sensor models on top of the capabilities of actual sensors have been provided.All of the proposed algorithms have been implemented either on real robots (for the case of individual robots) or in simulation (for the case of multiple robots), and experimental results are given.     

Application of digital enhancement techniques for groundwater exploration in a hard-rock terrain

Abstract

Geomorphological and geological features, namely landforms, rock units and geological structures, have a definite relationship with the occurrence and movement of groundwater in hard-rock crystalline formations. Exploration and exploitation of this sub-surface resource depend upon the understanding of expected subsurface hydrological conditions through surface expressions. The different types of digital enhancement techniques using remotely sensed data help in the extraction of specific features that act as groundwater indicators and ultimately lead to the preparation of maps indicating groundwater prospective zones. In this study, different enhancement techniques, such as linear stretching, band combination, filtering and edge enhancement, have been employed for deriving groundwater-controlling features in typical hard-rock crystalline formations of parts of the Raichur district, Karnataka, India. The qualitative evaluation of each enhanced output for its feature exhibitance has narrowed down the optimum operations to be performed for extracting all the groundwater-related features. The linear-stretched band data and specific false colour composite (FCC) have brought out the details on geology and geomorphology, while the various landforms have been highlighted by the FCC of principal-component analysis. The geological structures have been highlighted by filtering techniques. Band subtraction has brought out the vegetation along valley fills and moisture-laden lineaments. Based on the results achieved, a package has been suggested that can be used on an operational basis for groundwater targeting in typical hard-rock crystalline formations. It should be further used in conjunction with knowledge of local field conditions to aid the investigations made by remote sensing techniques.     

Multi-robot exploration and terrain coverage in an unknown environment

Terrain exploration and coverage are required for a variety of applications such as mine clearing, intrusion detection and other humanitarian missions like search and rescue operations, for example, fire or blast in a building. During an emergency situation within a building it is crucial to explore the area as fast as possible in order to search and find the wounded people and other hazards. On account of the prevailing breakdown of communication in indoor environments in some situations, it is suggested that the robots can communicate indirectly with the use of markings in the environment. The Spanning Tree Coverage (STC) method, proposed for this problem, suffers in environments that have partially occupied cells and narrow door openings between rooms. In this paper, we consider an extension of the Simultaneous Multiple STC (S-MSTC) algorithm, which we proposed in our previous work on multiple autonomous robots used in exploration and coverage in an unknown terrain. The proposed extended S-MSTC (ES-MSTC) uses ant-type robots to cover the terrain leaving marks on the terrain, which can be sensed by the robots and allow them to cover the terrain, similar to the nature of ants. This algorithm can handle partially occupied cells and narrow door openings in the terrain and performs a complete coverage of the surface regardless of the shape of the environment by constructing multiple spanning trees simultaneously. We present a simulation study and compare the performance of the ES-MSTC algorithm with other existing algorithms.     

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.     

Rough terrain mapping and classification for foothold selection in a walking robot

Although legged locomotion over a moderately rugged terrain can be accomplished by employing simple reactions to the ground contact information, a more effective approach, which allows predictively avoiding obstacles, requires a model of the environment and a control algorithm that takes this model into account when planning footsteps and leg movements. This article addresses the issues of terrain perception and modeling and foothold selection in a walking robot. An integrated system is presented that allows a legged robot to traverse previously unseen, uneven terrain using only onboard perception, provided that a reasonable general path is known. An efficient method for real‐time building of a local elevation map from sparse two‐dimensional (2D) range measurements of a miniature 2D laser scanner is described. The terrain mapping module supports a foothold selection algorithm, which employs unsupervised learning to create an adaptive decision surface. The robot can learn from realistic simulations; therefore no a priori expert‐given rules or parameters are used. The usefulness of our approach is demonstrated in experiments with the six‐legged robot Messor. We discuss the lessons learned in field tests and the modifications to our system that turned out to be essential for successful operation under real‐world conditions. © 2011 Wiley Periodicals, Inc.     

Combining mapping and partitioning exploration for NoC-based embedded systems

Networks on Chip (NoC) have emerged as the key paradigm for designing a scalable communication infrastructure for future Systems on Chip (SoC). An important issue in NoC design is how to map an application on this architecture and how to determine the hardware/software partition that satisfies the performance, cost and flexibility requirements. In this paper, we propose an approach that concurrently optimizes the mapping and the partitioning of streaming applications. The proposed approach exploits multiobjective evolutionary algorithms that are fed by execution performances scores corresponding to the evaluated mappings and partitioning ability to pipeline execution of the streaming application. As result, most promising solutions are highlighted for mapping multimedia applications onto a SoC architecture interconnecting 16 nodes through 2D-Mesh and Ring NoC.     

Visual exploration of complex time-varying graphs

Quasi-trees, namely graphs with tree-like structure, appear in many application domains, including bioinformatics and computer networks. Our new SPF approach exploits the structure of these graphs with a two-level approach to drawing, where the graph is decomposed into a tree of biconnected components. The low-level biconnected components are drawn with a force-directed approach that uses a spanning tree skeleton as a starting point for the layout. The higher-level structure of the graph is a true tree with meta-nodes of variable size that contain each biconnected component. That tree is drawn with a new area-aware variant of a tree drawing algorithm that handles high-degree nodes gracefully, at the cost of allowing edge-node overlaps. SPF performs an order of magnitude faster than the best previous approaches, while producing drawings of commensurate or improved quality