Traverse Planning with Temporal-Spatial Constraints

We present an approach to planning rover traverses in a domain that includes temporal-spatial constraints. We are using the NASA Resource Prospector mission as a reference mission in our research. The objective of this mission is to explore permanently shadowed regions at a Lunar pole. Most of the time the rover is required to avoid being in shadow. This requirement depends on where the rover is located and when it is at that location. Such a temporal-spatial constraint makes traverse planning more challenging for both humans and machines. We present a mixed-initiative traverse planner which addresses this challenge. This traverse planner is part of the Exploration Ground Data Systems (xGDS), which we have enhanced with new visualization features, new analysis tools, and new automation for path planning, in order to be applicable to the Re-source Prospector mission. The key concept that is the basis of the analysis tools and that supports the automated path planning is reachability in this dynamic environment due to the temporal-spatial constraints

Terrain Representation And Reasoning In Computer Generated Forces : A Survey Of Computer Generated Forces Systems And How They Represent And Reason About Terrain

Report on a survey of computer systems used to produce realistic or intelligent behavior by autonomous entities in simulation systems. In particular, it is concerned with the data structures used by computer generated forces systems to represent terrain and the algorithmic approaches used by those systems to reason about terrain

Path planning for mobile robots in the real world: handling multiple objectives, hierarchical structures and partial information

Autonomous robots in real-world environments face a number of challenges even to accomplish apparently simple tasks like moving to a given location. We present four realistic scenarios in which robot navigation takes into account partial information, hierarchical structures, and multiple objectives. We start by discussing navigation in indoor environments shared with people, where routes are characterized by effort, risk, and social impact. Next, we improve navigation by computing optimal trajectories and implementing human-friendly local navigation behaviors. Finally, we move to outdoor environments, where robots rely on uncertain traversability estimations and need to account for the risk of getting stuck or having to change route

Vision-based terrain classification and classifier fusion for planetary exploration rovers

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includes bibliographical references (leaves 63-66).Autonomous rover operation plays a key role in planetary exploration missions. Rover systems require more and more autonomous capabilities to improve efficiency and robustness. Rover mobility is one of the critical components that can directly affect mission success. Knowledge of the physical properties of the terrain surrounding a planetary exploration rover can be used to allow a rover system to fully exploit its mobility capabilities. Here a study of multi-sensor terrain classification for planetary rovers in Mars and Mars-like environments is presented. Supervised classification algorithms for color, texture, and range features are presented based on mixture of Gaussians modeling. Two techniques for merging the results of these "low level" classifiers are presented that rely on Bayesian fusion and meta-classifier fusion. The performances of these algorithms are studied using images from NASA's Mars Exploration Rover mission and through experiments on a four-wheeled test-bed rover operating in Mars-analog terrain. It is shown that accurate terrain classification can be achieved via classifier fusion from visual features.by Ibrahim Halatci.S.M

GIS approaches to understanding connections and movement through space

The overarching theme of this work is an exploration of ways in which GIS can be used to analyse connections or movement through space in a wide variety of contexts. The published work focuses upon the application of both network and raster-based techniques at a variety of scales. A review is provided summarising the breadth of applications that currently use GIS to model connectivity or movement through space. This is followed by a series of published work in this field. This includes both raster and network approaches to assessing journey-time exposure to air pollution; exploring the impact of artificial lighting on gap crossing thresholds of bats; examining the presence of food deserts in rainforest cities; assessing urban accessibility and its influence on social vulnerability to climate shocks; and understanding of the impact of segregation on everyday patterns of mobility. With a diverse range of application areas and variety of spatial scales ranging from 2 - 605,000km2, this published work highlights the ways in which GIS can be implemented in new ways to improve understanding of connections and/or movement through space

Terrain Aware Traverse Planning for Mars Rovers

NASA is proposing a Mars Sample Return mission, to be completed within one Martian year, that will require enhanced autonomy to perform its duties faster, safer, and more efficiently. With its main purpose being to retrieve samples possibly tens of kilometers away, it will need to drive beyond line-of-sight to get to its target more quickly than any rovers before. This research proposes a new methodology to support a sample return mission and is divided into three compo-nents: map preparation (map of traversability, i.e., ability of a terrain to sustain the traversal of a vehicle), path planning (pre-planning and replanning), and terrain analysis. The first component aims at creating a better knowledge of terrain traversability to support planning, by predicting rover slip and drive speed along the traverse using orbital data. By overlapping slope, rock abundance and terrain types at the same location, the expected drive velocity is obtained. By combining slope and thermal data, additional information about the experienced slip is derived, indicating whether it will be low (less than 30%) or medium to high (more than 30%). The second component involves planning the traverse for one Martian day (or sol) at a time, based on the map of expected drive speed. This research proposes to plan, offline, several paths traversable in one sol. Once online, the rover chooses the fastest option (the path cost being calculated using the distance divided by the expected velocity). During its drive, the rover monitors the terrain via analysis of its experienced wheel slip and actual speed. This information is then passed along the different pre-planned paths over a given distance (e.g., 25 m) and the map of traversability is locally updated given this new knowledge. When an update occurs, the rover calculates the new time of arrival of the various paths and replans its route if necessary. When tested in a simulation study on maps of the Columbia Hills, Mars, the rover successfully updates the map given new information drawn from a modified map used as ground truth for simulation purposes and replans its traverse when needed. The third component describes a method to assess the soil in-situ in case of dangerous terrain detected during the map update, or if the monitoring is not enough to confirm the traversability predicted by the map. The rover would deploy a shear vane instrument to compute intrinsic terrain parameters, information then propagated ahead of the rover to update the map and replan if necessary. Experiments in a laboratory setting as well as in the field showed promising results, the mounted shear vane giving values close to the expected terrain parameters of the tested soils

Roving vehicle motion control Final report

Roving vehicle motion control for unmanned planetary and lunar exploratio