SEARCH · Search NASA
Results for “rover science”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Exploring the Jezero Crater Floor: The Mars 2020 Perseverance Rover’s First Science Campaign
No abstract provided
Integrated Results from Analysis of the Rocknest Aeolian Deposit by the Curiosity Rover
The Mars Science Laboratory Curiosity rover spent 45 sols (from sol 56-101) at an area called Rocknest (Fig. 1), characterizing local geology and ingesting its aeolian fines into the analytical instruments CheMin and SAM for mineralogical and chemical analysis. Many abstracts at this meeting present the contextual information and detailed data on these first solid samples analyzed in detail by Curiosity at Rocknest. Here, we present an integrated view of the results from Rocknest - the general agreement from discussions among the entire MSL Science Team.
Closed loop control for autonomous approach and placement of science instruments by planetary rovers
This paper presents a novel, end-to-end fully integrated system being developed at JPL that is called SCAIP. SCAIP enables a rover to autonomously travel to a designated science target from an extended distance away, and precisely place an instrument on that target with a single command without additional human interaction.
Practical Operational Readiness Gambits: Operations Training Simulations for the Curiosity Rover
The Mars Science Laboratory team had been puttingin effort to make a Training Venue to allow for parallel shadowtactical operations for trainees to actively work alongside theprime tactical operations personnel without affecting operations,since staffing constraints and shortened operations timelineswere straining the tactical process in supporting operationstrainees in the traditional way. The COVID- 19 Pandemic presentedfurther challenges in continuing on-console training forMSL operations trainees. The MSL operations team switched tofully remote operations, thus hampering the direct mentorshipa trainee would normally receive while on site at JPL. TheMars 2020 training team had developed a concept for roveroperations training simulations based on Johnson Space Center’sextensive simulations training program for astronauts andflight controllers. The MSL team borrowed this idea, and implementedthese training simulations which are called PracticalOperational Readiness Gambits (PORGs). The PORGs so farhave focused on the Science Planner and Rover Planner roles,which are two crucial roles in tactical operations that engagein key interactions throughout a shift. PORGs are based onactual sol scenarios that have occurred on Mars and follow thetactical operations process and timeline as closely as possible.However, unlike an operations shift, PORGs can slow down orpause to allow for more mentoring time. PORGs can focus onparticular skills to test the trainees on their understanding ofa concept. PORGs increase in complexity with each scenario toease the trainees into more typical tactical operations workloads.As more trainees join the MSL operations team, more roles arebeing incorporated into PORGs. There are plans to incorporatecertified operations personnel into PORGs to practice anomalyresponse situations. PORGs have become an essential part of theMSL operations training program and will continue even afterthe return to on-site operations at JPL.
The Mars exploration rover: an in situ science mission to Mars
In this paper the concept for a mobile vehicle system which performs an in situ science mission to Mars is described. This rover mission with its requirements for driving, positioning at science selected targets, and remote and in situ measurement will utilize the technologies for hazard avoidance and autonomous navigation supported by ground operation tools which use rover-based imagery for position estimation and motion planning.
Mixed-Initiative Activity Planning for Mars Rovers
One of the ground tools used to operate the Mars Exploration Rovers is a mixed-initiative planning system called MAPGEN. The role of the system is to assist operators building daily plans for each of the rovers, maximizing science return, while maintaining rover safety and abiding by science and engineering constraints. In this paper, we describe the MAPGEN system, focusing on the mixed-initiative planning aspect. We note important challenges, both in terms of human interaction and in terms of automated reasoning requirements. We then describe the approaches taken in MAPGEN, focusing on the novel methods developed by our team.
Multi-Mission Terrain Classifier for Safe Rover Navigation and Automated Science
We previously presented Soil Property and Object Classification (SPOC), a machine learning-based terrain classifier for Mars rovers, for automatically segmenting rover images by its surface type such as sand and bedrock. This paper presents a number of practical improvements to pave the way for potential future onboard deployment. First, we achieved 97.0% overall pixel accuracy, evaluated against the classification generated by human experts on images from Mars Science Laboratory (MSL) missions. The substantial increase in accuracy was primarily enabled by the sheer volume of data used for training; we created a new large-scale dataset of Martian terrain labels, namely AI4Mars, which contains more than 400k labels contributed by citizen scientists for 50k images taken by the Mars Exploration Rovers (MER) and Mars Science Laboratory (MSL) rover. Second, we demonstrated that SPOC can quickly adapt to a new mission landed on a previously unseen site. Specifically, we pretrained a model with MER and MSL data from the AI4Mars dataset and then adapted to the Mars 2020 Rover (M2020) by feeding a small volume of data between Sol 0 and 157; the adapted model was tested on Sol 200-203 and resulted in 84.2% overall pixel accuracy and 93.4% reliability (recall) for detecting sand, the most concerning class for rover’s traversability. Third, we found that pretraining can substantially mitigate the decline of accuracy over time. We showed that the performance of a SPOC model pretrained with the ImageNet dataset and then trained by MSL images only up to Sol 390 remains comparable to a model trained by images up to Sol 1689 on the test data after Sol 1689. Fourth, we reimplemented SPOC with a light-weight convolutional neural network (CNN), MobileNetV2, which typically runs within tens of milliseconds (ms) on mobile processors such as Qualcomm’s Snapdragon. Finally, we released the AI4Mars dataset to the public to encourage open innovation.
Mars Exploration Rover Operations with the Science Activity Planner
The Science Activity Planner (SAP) is the primary science operations tool for the Mars Exploration Rover mission and NASA's Software of the Year for 2004. SAP utilizes a variety of visualization and planning capabilities to enable the mission operations team to direct the activities of the Spirit and Opportunity rovers. This paper outlines some of the challenging requirements that drove the design of SAP and discusses lessons learned from the development and use of SAP in mission operations.
Distributed Operations for the Mars Exploration Rover Mission with the Science Activity Planner
Due to the length of the Mars Exploration Rover Mission, most scientists were unable to stay at the central operations facility at the Jet Propulsion Laboratory. This created a need for distributed operations software, in the form of the Distributed Science Activity Planner. The distributed architecture saved a considerable amount of money and increased the number of individuals who could be actively involved in the mission, contributing to its success.
Autonomous Onboard Science Image Analysis for Future Mars Rover Missions
To explore high priority landing sites and to prepare for eventual human exploration, future Mars missions will involve rovers capable of traversing tens of kilometers. However, the current process by which scientists interact with a rover does not scale to such distances. Specifically, numerous command cycles are required to complete even simple tasks, such as, pointing the spectrometer at a variety of nearby rocks. In addition, the time required by scientists to interpret image data before new commands can be given and the limited amount of data that can be downlinked during a given command cycle constrain rover mobility and achievement of science goals. Experience with rover tests on Earth supports these concerns. As a result, traverses to science sites as identified in orbital images would require numerous science command cycles over a period of many weeks, months or even years, perhaps exceeding rover design life and other constraints. Autonomous onboard science analysis can address these problems in two ways. First, it will allow the rover to transmit only "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands. For example, a rover might autonomously acquire and return spectra of "interesting" rocks along with a high resolution image of those rocks in addition to returning the context images in which they were detected. Such approaches, coupled with appropriate navigational software, help to address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing fast, autonomous algorithms to enable such intelligent on-board decision making by spacecraft. Autonomous algorithms developed to date have the ability to identify rocks and layers in a scene, locate the horizon, and compress multi-spectral image data. Output from these algorithms could be used to autonomously obtain rock spectra, determine which images should be transmitted to the ground, or to aid in image compression. We will discuss these and other algorithms and demonstrate their performance during a recent rover field test.
Rovers for Mars Polar Exploration
Mobility is a generic capability needed for Mars exploration. Requirements for mobility range from those needed to get observations of individual rocks all the way to those for getting high-resolution observations of regional areas. The Pathfinder mission and field experiments simulating rover missions provide guidance as to rover capabilities that can reasonably be expected in the next decade. Success of rover missions in achieving science goals depends on having adequate support imaging to enable traverses to targets of high science interest. Rover field experiments to date have used aerial photographs to provide support imaging. Pathfinder Sojourner operated in the field of view of the IMP camera. Plans for the future involve the use of descent imagers. However, the descent imager planned for the 2001 mission achieves resolution adequate to plan rover traverses only in the near vicinity of the lander (within a few hundred meters). Aircraft could provide aerial support imaging with a resolution of 10 cm over the entire area accessible to a rover. Aircraft could also provide the mobility needed to explore regional scale areas
Using XRD to Characterize Sediment Sorting in a Mars Analog Glacio-Fluvio-Eolian Basaltic Sedimentary System in Iceland
The martian surface has a primarily basaltic composition and is dominated by sedimentary deposits. Ancient layered sedimentary rocks have been identified across the planet from orbit, have been studied in situ by the Mars Exploration Rovers and the Mars Science Laboratory rover, and will be studied by the Mars 2020 rover. These ancient sedimentary rocks were deposited in fluvial, lacustrine, and eolian environments during a warmer and wetter era on Mars. It is important to study the composition of sediments in Mars analog environments to characterize how minerals in basaltic sedimentary systems are sorted and/or aqueously altered. This information can help us better interpret sedimentary processes from similar deposits on Mars and derive information about the igneous source rocks. Sediment sorting has been studied extensively on Earth, but not typically in basaltic environments. Previous work has addressed sorting of basaltic sediments through experimental techniques and in modern eolian basaltic systems and aqueous alteration in subglacial and proglacial environments. We add to this body of research by studying sediment sorting and aqueous alteration in a glacio-fluvio-eolian basaltic system in southwest Iceland.
Mars Science Laboratory (MSL) : the US 2009 Mars rover mission
The Mars Science Laboratory mission is the 2009 United States Mars Exploration Program rover mission. The MSL Project expects to complete its pre-Phase A definition activity this fiscal year (FY2003), investigations in mid-March 2004, launch in 2009, arrive at Mars in 2010 during Northern hemisphere summer and then complete a full 687 day Mars year of surface exploration. MSL will assess the potential for habitability (past and present) of a carefully selected landing region on Mars by exploring for the chemical building blocks of life, and seeking to understand quantitatively the chemical and physical environment with which these components have interacted over the geologic history of the planet. Thus, MSL will advance substantially our understanding of the history of Mars and potentially, its capacity to sustain life.
The Preparation for and Execution of Engineering Operations for the Mars Curiosity Rover Mission
The Mars Science Laboratory Curiosity Rover mission is the most complex and scientifically packed rover that has ever been operated on the surface of Mars. The preparation leading up to the surface mission involved various tests, contingency planning and integration of plans between various teams and scientists for determining how operation of the spacecraft (s/c) would be facilitated. In addition, a focused set of initial set of health checks needed to be defined and created in order to ensure successful operation of rover subsystems before embarking on a two year science journey. This paper will define the role and responsibilities of the Engineering Operations team, the process involved in preparing the team for rover surface operations, the predefined engineering activities performed during the early portion of the mission, and the evaluation process used for initial and day to day spacecraft operational assessment.
Exploration of Mars with the ChemCam LIBS Instrument and the Curiosity Rover
The Mars Science Laboratory (MSL) Curiosity rover landed on Mars in August 2012, and has been exploring the planet ever since. Dr. Horton E. Newsom will discuss the MSL's design and main goal, which is to characterize past environments that may have been conducive to the evolution and sustainability of life. He will also discuss Curiosity's science payload, and remote sensing, analytical capabilities, and direct discoveries of the Chemistry & Camera (ChemCam) instrument, which is the first Laser Induced Breakdown Spectrometer (LIBS) to operate on another planetary surface and determine the chemistry of the rocks and soils.
Effect of the Presence of Chlorates and Perchlorates on the Pyrolysis of Organic Compounds: Implications for Measurements Done with the SAM Experiment Onboard the Curiosity Rover
The Mars Science Laboratory (MSL) Curiosity Rover carries a suite of instruments, one of which is the Sample Analysis at Mars (SAM) experiment. SAM is devoted to the in situ molecular analysis of gases evolving from solid samples collected by Curiosity on Mars surface/sub-surface. Among its three analytical devices, SAM has a gaschromatograph coupled to a quadrupole mass spectrometer (GC-QMS). The GC-QMS is devoted to the separation and identification of organic and inorganic material. Before proceeding to the GC-QMS analysis, the solid sample collected by Curiosity is subjected to a thermal treatment thanks to the pyrolysis oven to release the volatiles into the gas processing system. Depending on the sample, a derivatization method by wet chemistry: MTBSTFA of TMAH can also be applied to analyze the most refractory compounds. The GC is able to separate the organic molecules which are then detected and identified by the QMS (Figure 1). For the second time after the Viking landers in 1976, SAM detected chlorinated organic compounds with the pyrolysis GC-QMS experiment. The detection of perchlorates salts (ClO4-) in soil at the Phoenix Landing site suggests that the chlorohydrocarbons detected could come from the reaction of organics with oxychlorines. Indeed, laboratory pyrolysis experiments have demonstrated that oxychlorines decomposed into molecular oxygen and volatile chlorine (HCl and/or Cl2) when heated which then react with the organic matter in the solid samples by oxidation and/or chlorination processes.