The vehicles used to explore the Martian surface require a high degree of autonomy to navigate challenging and unknown terrain, investigate targets, and detect scientific events. Increased autonomy ...will be critical to the success of future missions. In July 1997, as part of NASA's Mars Pathfinder mission, the Sojourner rover became the first spacecraft to autonomously drive on another planet. The twin Mars Exploration Rovers (MER) vehicles landed in January 2004, and after four years Spirit had driven more than four miles and Opportunity more than seven miles-lasting well past their projected three-month lifetime and expected distances traveled. The newest member of the Mars rover family will have the ability to autonomously approach and inspect a target and automatically detect interesting scientific events. In fall 2009, NASA plans to launch the Mars Science Laboratory (MSL) rover, with a primary mission of two years of surface exploration and the ability to acquire and process rock samples. In the near future, the Mars Sample Return (MSR) mission, a cooperative project of NASA and the European Space Agency, will likely use a lightweight rover to drive out and collect samples and bring them back to an Earth return vehicle. This rover will use an unprecedented level of autonomy because of the limited lifetime of a return rocket on the Martian surface and the desire to obtain samples from distant crater walls.
Abstract
(1) Three practical and easily implementable methods are provided to estimate percent increases in extreme rainfall due to climate change for the period 2020–2090 using Global Climate Model ...(GCM) output. (2) Methods are designed to bracket the expected range of extreme rainfall intensification for 1–24-h events with return intervals of 1 year to 100 years. (3) One method is based on the 20 largest wet days produced by an ensemble of GCMs, and the other two use GCM projections of temperature and Clausius–Clapeyron assumptions. (4) The results of the case study for the Philadelphia area show that, by the end-of-century, extreme rain event volumes might increase from a low of 18% to a high of 61%, depending on the duration and return interval under consideration. (5) Methods have been benchmarked against existing, publicly available projected rainfall intensities to show the methods that provide an accurate range of extreme rainfall intensification due to climate change.
NASA's Mars Science Laboratory Curiosity rover landed in August 2012 and began experiencing higher rates of wheel damage beginning in October 2013. While the wheels were designed to accumulate ...considerable damage, the unexpected damage rate raised concerns regarding wheel lifetime. In response, the Jet Propulsion Laboratory developed and deployed mobility flight software on Curiosity that reduces the forces on the wheels. The new algorithm adapts each wheel's speed to fit the terrain topography in real time, by leveraging the rover's measured attitude rates and rocker/bogie suspension angles and rates. Together with a rigid‐body kinematics model, it estimates the real‐time wheel‐terrain contact angles and commands idealized, no‐slip wheel angular rates. In addition, free‐floating “wheelies” are detected and autonomously corrected. Ground test data indicate that the forces on the wheels are reduced by 19% for leading wheels and 11% for middle leading wheels. On the ground, the required data volume increased by up to 129%, and drive duration increased by up to 25%. In flight, data collected over 3.6 km and 149 drives confirmed a reduction in wheel current, correlated with wheel torque, of 18.7%. The new algorithm proved to use fewer resources in flight than ground estimates suggested, as only a 10% increase in drive duration and double the drive data volume were experienced. These data indicate the promise of the new algorithm to extend the life of the wheels for the Curiosity rover. This paper describes the algorithm, its ground testing campaign and associated challenges, and its validation, implementation, and performance in flight.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
It is anticipated that the Mars Science Laboratory rover, named Curiosity, will traverse 10–20 km on the surface of Mars during its primary mission. In preparation for this traverse, Earth‐based ...tests were performed using Mars weight vehicles. These vehicles were driven over Mars analog bedrock, cohesive soil, and cohesionless sand at various slopes. Vehicle slip was characterized on each of these terrains versus slope for direct upslope driving. Results show that slopes up to 22 degrees are traversable on smooth bedrock and that slopes up to 28 degrees are traversable on some cohesive soils. In cohesionless sand, results show a sharp transition between moderate slip on 10 degree slopes and vehicle embedding at 17 degrees. For cohesionless sand, data are also presented showing the relationship between vehicle slip and wheel sinkage. Side by side testing of the Mars Exploration Rover test vehicle and the Mars Science Laboratory test vehicle show how increased wheel diameter leads to better slope climbing ability in sand for vehicles with nearly identical ground pressure. Lastly, preliminary data from Curiosity's initial driving on Mars are presented and compared to the Earth‐based testing, showing good agreement for the driving done during the first 250 Martian days.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
NASA’s Mars Exploration Rovers (MER) have collected a great diversity of geological science results, thanks in large part to their surface mobility capabilities. The six wheel rocker/bogie mobility ...system provides driving capabilities in a range of terrain types, while the onboard IMU measures actual rover attitude changes (roll, pitch and yaw, but not position) quickly and accurately. Four stereo camera pairs provide accurate position knowledge and/or terrain assessment. Solar panels generally provide enough energy to drive the vehicle for at most four hours each day, but drive time is often restricted by other planned activities. Driving along slopes in nonhomogeneous terrain injects unpredictable amounts of slip into each drive. These restrictions led to the creation of driving strategies that alternately use more or less onboard autonomy, to maximize drive speed and distance at the cost of increased complexity in the sequences of commands built by human Rover Planners each day.
Commands to the MER vehicles are typically transmitted at most once per day, so mobility operations are encoded as event-driven sequences of individual motion commands. Motions may be commanded using quickly-executing Directed commands which perform only reactive motion safety checks (e.g., real-time current limits, maximum instantaneous vehicle tilt limit), slowly-executing position measuring Visual Odometry (VisOdom) commands, which use images to accurately update the onboard position estimate, or slow-to-medium speed Autonomous Navigation (AutoNav) commands, which use onboard image processing to perform predictive terrain safety checks and optional autonomous Path Selection.
In total, the MER rovers have driven more than 10 kilometers over Martian terrain during their first 21 months of operation using these basic modes. In this paper we describe the strategies adopted for selecting between human-planned Directed drives versus rover-adaptive Autonomous Navigation, Visual Odometry and Path Selection drives.
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Identifying and avoiding terrain hazards (e.g., soft soil and pointy embedded rocks) are crucial for the safety of planetary rovers. This paper presents a newly developed ground-based Mars rover ...operation tool that mitigates risks from terrain by automatically identifying hazards on the terrain, evaluating their risks, and suggesting operators safe paths options that avoids potential risks while achieving specified goals. The tool will bring benefits to rover operations by reducing operation cost, by reducing cognitive load of rover operators, by preventing human errors, and most importantly, by significantly reducing the risk of the loss of rovers. The risk-aware rover operation tool is built upon two technologies. The first technology is a machine learning-based terrain classification that is capable of identifying potential hazards, such as pointy rocks and soft terrains, from images. The second technology is a risk-aware path planner based on rapidly-exploring random graph (RRG) and the A* search algorithms, which is capable of avoiding hazards identified by the terrain classifier with explicitly considering wheel placement. We demonstrate the integrated capability of the proposed risk-aware rover operation tool by using the images taken by the Curiosity rover.
Abstract
Floods have been occurring with increasing frequency, leading to damage to communities worldwide. These impacts are expected to continue to rise due to increases in the intensity of extreme ...rainfall. Global climate model (GCM) output, while imperfect in reproducing daily rainfall, is the only practical source of future projections of extreme rainfall intensification. This article presents a practical method for translating GCM precipitation output into usable outputs for stormwater and flood management planning at a regional or local level. The method estimates the impact of extreme storm intensification on riverine flooding using available runoff estimates from GCM precipitation and variable infiltration capacity models, focusing on changes in elevation and frequency due to climate change. It allows communities and utilities to obtain a screening-level estimate of climate change impacts to peak discharge rate statistics without conducting hydrologic modeling. This article outlines the method, its implementation for the 48 contiguous states of the United States, and an example calculation for a river in the eastern United States. Changes in extreme storm runoff intensity vary significantly by region, but much of the United States is projected to see increases of 25 and 50% by 2060 and 2090, respectively, for the RCP8.5 scenario.
NASA's Mars Exploration Rover (MER) missions will land twin rovers on the surface of Mars in 2004. These rovers will have the ability to navigate safely through unknown and potentially hazardous ...terrain, using autonomous passive stereo vision to detect potential terrain hazards before driving into them. Unfortunately, the computational power of currently available radiation hardened processors limits the amount of distance (and therefore science) that can be safely achieved by any rover in a given time frame. We present overviews of our current rover vision and navigation systems, to provide context for the types of computation that are required to navigate safely. We also present baseline timing results that represent a lower bound in achievable performance (useful for systems engineering studies of future missions), and describe ways to improve that performance using commercial grade (as opposed to radiation hardened) processors. In particular, we document speedups to our stereo vision system that were achieved using the vectorized operations provided by Pentium MMX technology. Timing data were derived from implementations on several platforms: a prototype Mars rover with flight-like electronics (the Athena Software Development Model (SDM) rover), a RAD6000 computing platform (as will be used in the 2003 MER missions), and research platforms with commercial Pentium III and Sparc processors. Finally, we summarize the radiation effects analysis that suggests that commercial grade processors are likely to be adequate for Mars surface missions, and discuss the level of speedup that may accrue from using these instead of radiation hardened parts.
Visual odometry on the Mars Exploration Rovers Yang Cheng; Mark Maimone; Larry Matthies
2005 IEEE International Conference on Systems, Man and Cybernetics,
2005, Volume:
1
Conference Proceeding
NASA's Mars Exploration Rovers (MER) was designed to traverse in Viking Lander-I style terrains: mostly flat, with many small non-obstacle rocks and occasional obstacles. During actual operations in ...such terrains, onboard position estimates derived solely from the onboard inertial measurement unit and wheel encoder-based odometry achieved well within the design goal of at most 10% error. However, MER vehicles were also driven along slippery slopes tilted as high as 31 degrees. In such conditions an additional capability was employed to maintain a sufficiently accurate onboard position estimate: visual odometry. The MER visual odometry system comprises onboard software for comparing stereo pairs taken by the pointable mast-mounted 45 degree FOV navigation cameras (NAV-CAMs). The system computes an update to the 6-DOF rover pose (x, y, z, roll, pitch, yaw) by tracking the motion of autonomously-selected "interesting" terrain features between two pairs of stereo images, in both 2D pixel and 3D world coordinates. A maximum likelihood estimator is applied to the computed 3D offsets to produce a final, corrected estimate of vehicle motion between the two pairs. In this paper we describe the visual odometry algorithm used on the Mars Exploration Rovers, and summarize its results from the first year of operations on Mars.
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