Lunar Orbiter 1, preliminary results - Lunar terrain assessment and selenodesy, micrometeoroid, and radiation measurements
Lunar Orbiter 1 terrain assessment photographs and preliminary selenodesy, micrometeoroid, and radiation data
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Lunar Orbiter 1 terrain assessment photographs and preliminary selenodesy, micrometeoroid, and radiation data
This paper presents novel measures of terrain traversability at three different scales of resolution; namely local, regional, and global traversability indices.
In this paper we develop a methodology based on ballistics to estimate the landing footprint associated with the powered terminal descent phase of a Mars soft landing.
This paper presents a novel technique for real-time measurement of terrain characteristics and incorporation of this information into the navigation strategy of an autonomous mobile robot.
In August 2012, the Mars Science Laboratory (MSL) mission will pioneer the next generation of robotic Entry, Descent, and Landing (EDL) systems by delivering the largest and most capable rover to date to the surface of Mars. The process to select the MSL landing site took over five years and began with over 50 initial candidate sites from which four finalist sites were chosen. The four finalist sites were examined in detail to assess overall science merit, EDL safety, and rover traversability on the surface. Ultimately, the engineering assessments demonstrated a high level of safety and robustness at all four finalist sites and differences in the assessment across those sites were small enough that neither EDL safety nor rover traversability considerations could significantly discriminate among the final four sites. Thus the MSL landing site at Gale Crater was selected from among the four finalists primarily on the basis of science considerations.
Widely used to calculate illumination geometry forestimates of solar and emitted longwave radiation, and forcorrecting remotely sensed data for topographic effects, digitalelevation models (DEMs) are now extensive globally at 10–30-mspatial resolution and locally at spatial resolutions down to afew centimeters. Globally, regionally, or locally, elevation datasetshave many grid points. Many software packages calculate gradi-ents over every grid cell or point, but in the mountains, shadingby nearby terrain must also be assessed. Terrain may obscure aslope that would otherwise face the Sun. Four decadesago, a fastmethod to calculate topographic horizons at every point in anelevation grid required computations related only linearly to thesize of the grid, but grids now have so many points that parallelcomputing still provides an advantage. Exploiting parallelismover terrain grids can use alternative strategies: among columnsof a rotated grid, or simultaneously at multiple rotation angles,or on different tiles of a grid. On a multi-processor machine, theimprovement in computing time approaches 2/3 the number ofprocessors deployed,
This paper presents a technique for learning to assess terrain traversability for outdoor mobile robot navigation using human-embedded logic and real-time perception of terrain features extracted from image data.
The ocean world Europa is a prime target forexploration given its potential habitability [1]. We proposea mobile robotic system that is capable of autonomouslytraversing hundreds of meters to visit multiple sites of intereston a Europan analogue surface. Due to the topology of Europanterrain being largely unknown, it is desired that this mobilitysystem traverse a large variety of terrain types. The mobilitysystem should also be capable of crossing unstructured terrainin an autonomous manner given the communications limitationsbetween Earth and Europa.A wheel-on-limb robotic rover is presented that may activelyconform to terrain features up to 1.5 wheel diameters tall whiledriving. The robot uses a sampling-based motion planner togenerate paths that leverage its unique locomotive capabilities.The planner assesses terrain hazards and wheel workspacelimits as obstacles. It may also select a mobility mode basedon predicted energy usage and the need for limb articulationon the terrain being traversed. This autonomous mobility wasevaluated on the chaotic salt-evaporite terrain found in DeathValley, CA, an analogue to the Europan surface. Over the courseof 38 trials, the rover autonomously traversed 435m of extremeterrain while maintaining a rate of 0.64 traverse ending failuresfor every 10m driven.
To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover (MER) project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting tool, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction Simulator), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using MSC-Adams dynamic modeling software. Newly modeled terrain-rover interactions include the rut-formation effect of deformable soils, using the classical Bekker-Wong implementation of compaction resistances and bull-dozing effects. The paper presents the details and implementation of the model with two case studies based on actual MER telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.
To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting system, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction System), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using Adams dynamic modeling software. The external library was built in Fortran and called by Adams to model the wheel-soil interactions include the rut-formation effect of deformable soils, lateral and longitudinal forces, bull-dozing effects, and applied wheel torque. The paper presents the details and implementation of the system. To validate the developed system, one study case is presented from a realistic drive on Mars of the Opportunity rover. The simulation results match well from the measurement of on-board telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.
Robotic reconnaissance has the potential to significantly improve scientific and technical return from lunar surface exploration. In particular, robotic recon may increase crew productivity and reduce operational risk for exploration. However, additional research, development and field-testing is needed to mature robot and ground control systems, refine operational protocols, and specify detailed requirements. When the new lunar surface campaign begins around 2020, and before permanent outposts are established, humans will initially be on the Moon less than 10% of the time. During the 90% of time between crew visits, robots will be available to perform surface operations under ground control. Understanding how robotic systems can best address surface science needs, therefore, becomes a central issue Prior to surface missions, lunar orbiters (LRO, Kaguya, Chandrayyan-1, etc.) will map the Moon. These orbital missions will provide numerous types of maps: visible photography, topographic, mineralogical and geochemical distributions, etc. However, remote sensing data will not be of sufficient resolution, lighting, nor view angle, to fully optimize pre-human exploration planning, e.g., crew traverses for field geology and geophysics. Thus, it is important to acquire supplemental and complementary surface data. Robotic recon can obtain such data, using robot-mounted instruments to scout the surface and subsurface at resolutions and at viewpoints not achievable from orbit. This data can then be used to select locations for detailed field activity and prioritize targets to improve crew productivity. Surface data can also help identify and assess terrain hazards, and evaluate alternate routes to reduce operational risk. Robotic recon could be done months in advance, or be part of a continuing planning process during human missions.
Terrain Relative Navigation (TRN) was a critical enabling Entry, Descent, and Landing (EDL) technology that enabled Mars 2020 mission Perseverance rover to land at Jezero crater. TRN pro-vides real-time, autonomous, map-relative position determination and generates a landing target based on a priori knowledge of hazards. The required performance for TRN was to land within 60m of the selected target. The required 60m was sub-allocated to various error sources in three major categories: targeting error, knowledge error, and control error. The targeting error is the error in selecting an appropriate landing target and the knowledge of the target on the surface. It includes the Lander Vision System (LVS) position localization with respect the ground, the synchronization between the Lander Vision System measurement and the main Navigation filter, and errors associated with the LVS Reference Map and Safe Target Selec-tion (STS). The knowledge error is the contribution of knowledge growth from the synchronization with LVS to touchdown. The control error encompasses how accurately the system could stay on the desired reference trajectory. The TRN error budget uses a combination of analysis, simulation, and hardware test-ing results to bound the various error contributions obtained during the verification and validation process. This paper first presents a description the TRN system, focusing on the architecture of LVS and STS. The paper then gives detailed overview of the TRN error budget, with a description of the major error contribu-tions in each of the three categories. Next, the paper gives the results for three versions of the error budget, pre-launch, in-flight pre-landing, and post-landing. The paper compares the pre-flight analysis, the pre-landing analysis using in-flight data during cruise, to the post-landing analysis of the TRN performance. Pre-landing analysis best estimate of the landing performance was 33m, compared to the 60m require-ment. Post-landing analysis estimated a landing accuracy of 8.53m or better, much better than the 33m pre-landing estimate. The actual post-landing imagery calculated the distance of the rover to the targeted location to be 5m. The post-landing analysis closely bounds the image-based assessment of landing accu-racy, indicating the success of the error budget architecture in bounding the landing accuracy, as well as the fidelity of the simulations used to model and predict performance.
No abstract provided
This paper presents a novel tiered sensor fusion methodology for real-time terrain safety assessment. A combination of active and passive sensors, specifically, radar, lidar, and camera, operate in three tiers according to their inherent ranges of operation. Low-level terrain features (e.g. slope, roughness) and high-level terrain features (e.g. hills, craters) are integrated using principles of reasoning under uncertainty. Three methodologies are used to infer landing safety: Fuzzy Reasoning, Probabilistic Reasoning, and Evidential Reasoning. The safe landing predictions from the three fusion engines are consolidated in a subsequent decision fusion stage aimed at combining the strengths of each fusion methodology. Results from simulated spacecraft descents are presented and discussed.
Abstract Uncrewed aircraft system (UAS) observations collected during the 2018 Lower Atmospheric Process Studies at Elevation—a Remotely Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting Model using an ensemble Kalman filter. The benefit of UAS observations was assessed for a terrain-driven (drainage and upvalley) flow event that occurred within Colorado’s San Luis Valley (SLV) using independent observations. The analysis and prediction of the strength, depth, and horizontal extent of drainage flow from the Saguache Canyon and the subsequent transition to upvalley and up-canyon flow were improved relative to that obtained both without data assimilation (benchmark) and when only surface observations were assimilated. Assimilation of UAS observations greatly improved the analyses of vertical variations in temperature, relative humidity, and winds at multiple locations in the northern portion of the SLV, with reductions in both bias and the root-mean-square error of roughly 40% for each variable relative to the benchmark run. Despite these noted improvements, some biases remain that were tied to measurement error and/or the impact of the boundary layer parameterization on vertically spreading the observations, both of which require further exploration. The results presented here highlight how observations obtained with a fleet of profiling UAS improve limited-area, high-resolution analyses and short-term forecasts in complex terrain.
Rovers are the state of the art for the exploration and detection of past habitability and life on other worlds. One of the most basic functions of a rover is terrain navigation. Information collected by the rover is used autonomously to mitigate terrain hazards such large rocks, while humans qualitatively assess hazardous geologic terrain such as soil type and degree of rock cover. Planetary scientists use the same information to select targets such as drill sites, and for basic scientific analysis such as characterization of rock outcrops. Although the data is complementary, data from terrain analysis for navigation and terrain analysis for scientific investigations are poorly integrated. The lack of integration creates science and operation inefficiencies that limit exploration of habitable environments. As new modes of exploration come online, such as unmanned aerial systems (UAS) (e.g., the Mars Helicopter Scout and Titan Dragonfly), a need exists to integrate terrain data and science analysis to improve operational and scientific outcomes during exploration. We present an overview of a project aimed at evaluating the effectiveness and capability rover and UAS-based semi-automated terrain analysis using the Automated Soil Assessment Systems (ASAS) developed by Mission Control Space Services for navigating, selecting targets for sampling, and characterizing mafic detrital sediments along glacio-fluvial-aeolian sand transport pathways in Iceland. We describe recent advances in automated terrain analysis in sandy environments and scientific uses of terrain assessment from sandy environments. We assess fluvial and aeolian terrains in Iceland and show how terrain analysis data can inform scientific characterization of these environments.
The regions anitpodal to Mars' three largest impact basins, Hellas, Isidis, and Argyre, were assessed for evidence of impact-induced disrupted terrains. Photogeology and computer modeling using the Simplified Arbitrary Lagrangian Eulerian (SALE) finite element code suggest that such terrains could have been found by the Hellas impact. Maximum antipodal pressures are 1100 MPa for Hellas, 520 MPa for Isidis, and 150 MPa for Argyre. The results suggest that if antipodal fracturing were associated with later volcanism, then Alba Patera may be related to the Hellas event, as proposed by Peterson (1978). Alba Patera is a unique volcano in the solar system, being a shield volcano which emitted large volume lava flows. This volcanism could be the result of the focusing of seismic energy which created a fractured region that served as a volcanic conduit for the future release of large volumes of magma. No disrupted terrain features are observed antipodal to the Isidis or Argyre basins, although some of the old fractures in Noctis Labyrinthus could have originated in response to the Isidis impact, and later have been reactivated by the Tharsis tectonics assumed to have produced Noctis. If the lower calculated antipodal pressures for Argyre were capable of producing disrupted terrains, then the terrains have been covered subsequently by volcanic or aeolian material, or modified beyond recognition.
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