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At least 397 records · Page 22

Thermal Development of the Mars 2020 Enhanced Engineering Cameras

The engineering cameras (ECAMs) of the 2003 Mars Exploration Rover (MER) mission were re-flown on the Mars Science Laboratory (MSL) mission that launched in 2011. The upcoming Mars 2020 rover mission will introduce a new fleet of cameras called the enhanced engineering cameras (EECAMs). These EECAMs will have improved imaging capability, as the technology of the past ECAMs flown on Mars surface missions have become outdated. The EECAMs include six upgraded HazCams, two upgraded NavCams, and a single, newly-conceived CacheCam. The purposes of the HazCams and NavCams remain the same as they were for MER and MSL: to detect hazards to the front and rear of the rover, and to help in navigation across the Martian surface. The CacheCam will be used to take images of samples obtained by the rover’s Sample Caching System. This paper compares the differences in the thermal designs of the ECAMs and EECAMs, their design drivers, and their implications for the mission operations of the Mars 2020 rover.

Novak, Keith S.↗

Refactoring the Curiosity Rover's sample handling architecture on Mars

The Curiosity Mars rover sample handling hardware and software were architected assuming that end-to-end sampling operations would occur in a single rover position, from acquisition of a powdered sample with a scoop or drill, through to the cleaning out of all sample residue in the sample chain. However, after analysis of the first drilled samples in Yellowknife Bay, the science team wanted to iterate with additional experiments on Mars and in laboratories on Earth to better understand their results and increase the value of science returned. With the architecture as conceived, the time needed to do so was in direct competition with the exploration of other targets and satisfaction of success criteria during the prime mission.

Kuhn, Stephen↗

The Mars Exploration Rover/Collaborative Information Portal

Astrology has long argued that the alignment of the planets governs human affairs. Science usually scoffs at this. There is, however, an important exception: sending spacecraft for planetary exploration. In late May and early June, 2003, Mars will be in position for Earth launch. Two Mars Exploration Rovers (MER) will rocket towards the red planet. The rovers will perform a series of geological and meteorological experiments, seeking to examine geological evidence for water and conditions once favorable for life. Back on earth, a small army of surface operations staff will work to keep the rovers running, sending directions for each day's operations and receiving the files encoding the outputs of the Rover's six instruments. (Mars is twenty light minutes from Earth. The rovers must be robots.) The fundamental purpose of the project is, after all, Science. Scientists have experiments they want to run. Ideally, scientists want to be immediately notified when the data products of their experiments have been received, so that they can examine their data and (collaboratively) deduce results. Mars is an unpredictable environment. We may issue commands to the rovers but there is considerable uncertainty in how the commands will be executed and whether what the rovers sense will be worthy of further pursuit. The steps of what is, to a scientist, conceptually an individual experiment may be scattered over a large number of activities. While the scientific staff has an overall strategic idea of what it would like to accomplish, activities are planned daily. The data and surprises of the previous day need to be integrated into the negotiations for the next day's activities, all synchronized to a schedule of transmission windows . Negotiations is the operative term, as different scientists want the resources to run possibly incompatible experiments. Many meetings plan each day's activities.

Walton, Joan↗

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.

Mars rover athena instruments hazard detection haz↗

Automating Surface Attitude Positioning and Pointing Operations for Mars 2020

The Surface Attitude Positioning and Pointing (SAPP) subsystem of the Mars Perseverance rover keeps track of the rover’s position and attitude on the surface of Mars. The SAPP Downlink Engineering Operations team members receive data from the rover on a daily basis. They must interpret the data to make sure the rover is staying safe and to support uplink planning. The SAPP team keeps track of the error growth in the rover’s attitude estimate due to noise in the Rover Inertial Measurement Unit’s (RIMU) gyroscopes used to propagate that attitude estimate whenever the rover is moving. Whenever this error grows to a particular threshold, SAPP is responsible for updating the onboard attitude knowledge using the RIMU’s accelerometers to estimate rover roll and pitch and sun imaging to estimate rover yaw, thereby reducing this attitude estimation error. Accurate attitude estimation is required so that the rover can successfully point its High Gain Antenna (HGA) to receive information from Earth and as a backup to the Mars orbiters used for sending data from the rover to Earth, point instruments on its Remote Sensing Mast (RSM), and support safe movement and placement of instruments by the rover’s ARM relative to the Martian surface. The Mars 2020 Engineering Operations team has been working to increase the operational efficiency of the mission and eventually move to a five-hour timeline for daily operations. In pursuit of this goal, the SAPP Engineering Operations team has automated their downlink process by developing a centralized Jupyter notebook to analyze the data received daily from the rover. The SAPP downlink Jupyter notebook automatically collects the data relevant to the SAPP subsystem and visualizes this information in plots and tables that can be easily read by downlink operators to aid them in assessing the status of the subsystem. Various Application Programming Interfaces (APIs) have been incorporated into the downlink daily notebook to automate the collection and posting of data, such as gathering and posting data products to the cloud. The SAPP team has also developed a SAPP downlink software library that includes functions to aid the notebook in processing data. In addition to assessing the SAPP subsystem on a daily basis, operators need to assess the long-term trending behavior of the subsystem over time. An automated trending process has been developed to collect information from the daily notebooks in order to plot and analyze that data in a centralized place. These daily and trending processes have expedited the SAPP downlink assessment and laid the groundwork to completely automate the SAPP downlink process so that SAPP operators are unnecessary unless something unexpected occurs. This paper will provide an overview of the functions that the SAPP subsystem carries out on a daily basis, and will then dive into the automations that have been developed for daily and trending downlink assessment. An assessment of the downlink efficiency will be provided, along with a summary of lessons learned and work to go. Finally, the authors will discuss how these types of automated spacecraft health assessments could be more broadly used within mission operations.

Zarifian, Anais↗

Orchestrator Telemetry Processing Pipeline

Orchestrator is a software application infrastructure for telemetry monitoring, logging, processing, and distribution. The architecture has been applied to support operations of a variety of planetary rovers. Built in Java with the Eclipse Rich Client Platform, Orchestrator can run on most commonly used operating systems. The pipeline supports configurable parallel processing that can significantly reduce the time needed to process a large volume of data products. Processors in the pipeline implement a simple Java interface and declare their required input from upstream processors. Orchestrator is programmatically constructed by specifying a list of Java processor classes that are initiated at runtime to form the pipeline. Input dependencies are checked at runtime. Fault tolerance can be configured to attempt continuation of processing in the event of an error or failed input dependency if possible, or to abort further processing when an error is detected. This innovation also provides support for Java Message Service broadcasts of telemetry objects to clients and provides a file system and relational database logging of telemetry. Orchestrator supports remote monitoring and control of the pipeline using browser-based JMX controls and provides several integration paths for pre-compiled legacy data processors. At the time of this reporting, the Orchestrator architecture has been used by four NASA customers to build telemetry pipelines to support field operations. Example applications include high-volume stereo image capture and processing, simultaneous data monitoring and logging from multiple vehicles. Example telemetry processors used in field test operations support include vehicle position, attitude, articulation, GPS location, power, and stereo images.

Powell, Mark↗

Precision Instrument Targeting via Image Registration for the Mars 2020 Rover

A key component of Mars exploration is the operation of robotic instruments on the surface, such as those on board the Mars Exploration Rovers, the Mars Science Laboratory (MSL), and the planned Mars 2020 Rover. As the instruments carried by these rovers have become more advanced, the area targeted by some instruments becomes smaller, revealing more fine-grained details about the geology and chemistry of rocks on the surface. However, thermal fluctuations, rover settling or slipping, and inherent inaccuracies in pointing mechanisms all lead to pointing error that is on the order of the target size (several millimeters) or larger. We show that given a target located on a previously acquired image, the rover can align this with a new image to visually locate the target and refine the current pointing. Due to round-trip communication constraints, this visual targeting must be done efficiently on board the rover using relatively limited computing hardware. We employ existing ORB features for landmark-based image registration, describe and theoretically justify a novel approach to filtering false landmark matches, and employ a random forest classifier to automatically reject failed alignments. We demonstrate the efficacy of our approach using over 3,800 images acquired by Remote Micro-Imager on board the “Curiosity” rover.

Doran, Gary↗

Designing Facilities for Collaborative Operations

A methodology for designing operational facilities for collaboration by multiple experts has begun to take shape as an outgrowth of a project to design such facilities for scientific operations of the planned 2003 Mars Exploration Rover (MER) mission. The methodology could also be applicable to the design of military "situation rooms" and other facilities for terrestrial missions. It was recognized in this project that modern mission operations depend heavily upon the collaborative use of computers. It was further recognized that tests have shown that layout of a facility exerts a dramatic effect on the efficiency and endurance of the operations staff. The facility designs (for example, see figure) and the methodology developed during the project reflect this recognition. One element of the methodology is a metric, called effective capacity, that was created for use in evaluating proposed MER operational facilities and may also be useful for evaluating other collaboration spaces, including meeting rooms and military situation rooms. The effective capacity of a facility is defined as the number of people in the facility who can be meaningfully engaged in its operations. A person is considered to be meaningfully engaged if the person can (1) see, hear, and communicate with everyone else present; (2) see the material under discussion (typically data on a piece of paper, computer monitor, or projection screen); and (3) provide input to the product under development by the group. The effective capacity of a facility is less than the number of people that can physically fit in the facility. For example, a typical office that contains a desktop computer has an effective capacity of .4, while a small conference room that contains a projection screen has an effective capacity of around 10. Little or no benefit would be derived from allowing the number of persons in an operational facility to exceed its effective capacity: At best, the operations staff would be underutilized; at worst, operational performance would deteriorate. Elements of this methodology were applied to the design of three operations facilities for a series of rover field tests. These tests were observed by human-factors researchers and their conclusions are being used to refine and extend the methodology to be used in the final design of the MER operations facility. Further work is underway to evaluate the use of personal digital assistant (PDA) units as portable input interfaces and communication devices in future mission operations facilities. A PDA equipped for wireless communication and Ethernet, Bluetooth, or another networking technology would cost less than a complete computer system, and would enable a collaborator to communicate electronically with computers and with other collaborators while moving freely within the virtual environment created by a shared immersive graphical display.

Norris, Jeffrey↗

Automated Targeting for the MER Rovers

The Autonomous Exploration for Gathering Increased Science System (AEGIS) will soon provide automated targeting for remote sensing instruments on the Mars Exploration Rover (MER) mission, which currently which currently has two rovers exploring the surface of Mars. Currently, targets for rover remote-sensing instruments, especially narrow field-of-view instruments (such as the MER Mini- TES spectrometer or the 2011 Mars Science Laboratory (MSL) Mission ChemCam Spectrometer), must be selected manually based on imagery already on the ground with the operations team. AEGIS enables the rover flight software to analyze imagery onboard in order to autonomously select and sequence targeted remote-sensing observations in an opportunistic fashion. In this paper, we first provide some background information on the larger autonomous science framework in which AEGIS was developed. We then describe how AEGIS was specifically developed and tested on the JPL FIDO rover. Finally we discuss how AEGIS will be uploaded and used on the Mars Exploration Rover (MER) mission in early 2009.

rover autonomy↗

Attempt of Serendipitous Science During the Mojave Volatile Prospector Field Expedition

On 23 October a partial solar eclipse occurred across parts of the southwest United States between approximately 21:09 and 23:40 (UT), with maximum obscuration, 36%, occurring at 22:29 (UT). During 21-26 October 2014 the Mojave Volatile Prospector (MVP) field expedition deployed and operated the NASA Ames Krex2 rover in the Mojave desert west of Baker, California (Fig. 1, bottom). The MVP field expedition primary goal was to characterize the surface and sub-surface soil moisture properties within desert alluvial fans, and as a secondary goal to provide mission operations simulations of the Resource Prospector (RP) mission to a Lunar pole. The partial solar eclipse provided an opportunity during MVP operations to address serendipitous science. Science instruments on Krex2 included a neutron spectrometer, a near-infrared spectrometer with associated imaging camera, and an independent camera coupled with software to characterize the surface textures of the areas encountered. All of these devices are focused upon the surface and as a result are downward looking. In addition to these science instruments, two hazard cameras are mounted on Krex2. The chief device used to monitor the partial solar eclipse was the engineering development unit of the Near-Infrared Volatile Spectrometer System (NIRVSS) near-infrared spectrometer. This device uses two separate fiber optic fed Hadamard transform spectrometers. The short-wave and long-wave spectrometers measure the 1600-2400 and 2300-3400 nm wavelength regions with resolutions of 10 and 13 nm, respectively. Data are obtained approximately every 8 seconds. The NIRVSS stares in the opposite direction as the front Krex2.

soil moisture properties↗

Lunar Rover Localization Using Craters as Landmarks

Onboard localization capabilities for planetary rovers to date have used relative navigation, by integrating combinations of wheel odometry, visual odometry, and inertial measurements during each drive to track position relative to the start of each drive. At the end of each drive, a “ground-in-the-loop” (GITL) interaction is used to get a position update from human operators in a more global reference frame, such as a map frame defined by orbital reconnaissance imaging of a large region around the rover’s current position. For Mars rovers, this typically has involved downlinking imagery from the rover mast cameras and using interactive visualization tools on Earth to register such images to the orbital reconnaissance images. For safety purposes, rover mission operations typically specify “keep out zones”, which human operators recognize as being unsafe in the orbital images. Autonomous rover drives are limited in distance so that accumulated relative navigation error does not risk the possibility of the rover driving into a keep out zone. The allowable autonomous drive distance in this mode of operation depends on the distribution of keep out zones and the accuracy of relative navigation; in practice, drive limits of a few hundred meters between GITL cycles are to be expected. Several rover mission concepts have recently been studied that require much longer drives between GITL cycles, particularly for the Moon. This includes lunar rover mission concepts that involve (1) driving mostly in sunlight at low latitudes, (2) driving in permanently shadowed regions near the south pole, and (3) a mixture of day and night driving in mid-latitudes. These concepts include total traverse distance requirements of up to 1,800 km in 4 Earth years, with individual drives of several kilometers between stops for downlink. These concepts require greater autonomy to minimize GITL cycles to enable such large range; onboard global localization is a key element of such autonomy. Multiple techniques have been studied in the past for onboard rover global localization, including radio navigation aiding from an orbiter, recognizing horizon landmarks that are known in a regional elevation map, and correlating a local elevation map created onboard the rover with a regional elevation map. These techniques all have drawbacks, including requiring an expensive extra mission element (navigation orbiter), unavailability of sufficient regional elevation map data, or limited accuracy in resulting position estimates (e.g. a few hundred meters with horizon landmarks). For the Moon, the ubiquitous craters offer another possibility, which involves mapping craters from orbit, then recognizing crater landmarks with cameras and/or a lidar onboard the rover. This approach is applicable everywhere on the Moon, does not require high resolution stereo imaging from orbit as some other approaches do, and has potential to enable position knowledge with order of 10 m accuracy at all times. This paper will provide more detail on our technical approach to crater-based lunar rover localization and will present initial results on crater detection using 3-D point cloud data from onboard lidar or stereo cameras and using shading cues in monocular onboard imagery.

Ono, M.↗

Automatic Command Sequence Generation

Automatic Sequence Generator (Autogen) Version 3.0 software automatically generates command sequences for the Mars Reconnaissance Orbiter (MRO) and several other JPL spacecraft operated by the multi-mission support team. Autogen uses standard JPL sequencing tools like APGEN, ASP, SEQGEN, and the DOM database to automate the generation of uplink command products, Spacecraft Command Message Format (SCMF) files, and the corresponding ground command products, DSN Keywords Files (DKF). Autogen supports all the major multi-mission mission phases including the cruise, aerobraking, mapping/science, and relay mission phases. Autogen is a Perl script, which functions within the mission operations UNIX environment. It consists of two parts: a set of model files and the autogen Perl script. Autogen encodes the behaviors of the system into a model and encodes algorithms for context sensitive customizations of the modeled behaviors. The model includes knowledge of different mission phases and how the resultant command products must differ for these phases. The executable software portion of Autogen, automates the setup and use of APGEN for constructing a spacecraft activity sequence file (SASF). The setup includes file retrieval through the DOM (Distributed Object Manager), an object database used to store project files. This step retrieves all the needed input files for generating the command products. Depending on the mission phase, Autogen also uses the ASP (Automated Sequence Processor) and SEQGEN to generate the command product sent to the spacecraft. Autogen also provides the means for customizing sequences through the use of configuration files. By automating the majority of the sequencing generation process, Autogen eliminates many sequence generation errors commonly introduced by manually constructing spacecraft command sequences. Through the layering of commands into the sequence by a series of scheduling algorithms, users are able to rapidly and reliably construct the desired uplink command products. With the aid of Autogen, sequences may be produced in a matter of hours instead of weeks, with a significant reduction in the number of people on the sequence team. As a result, the uplink product generation process is significantly streamlined and mission risk is significantly reduced. Autogen is used for operations of MRO, Mars Global Surveyor (MGS), Mars Exploration Rover (MER), Mars Odyssey, and will be used for operations of Phoenix. Autogen Version 3.0 is the operational version of Autogen including the MRO adaptation for the cruise mission phase, and was also used for development of the aerobraking and mapping mission phases for MRO.

Fisher, Forest↗

Habitability Considerations for a Notional Five-Day Small Pressurized Rover Excursion

Within the Artemis program, the Pressurized Rover (PR) is intended to support two-person mobile habitation up to roughly thirty days in duration. Lunar surface use of the PR, however, assumes a crew swap approximately halfway through a 33-day surface mission. Within that shorter duration, a rover crew may perform one or more excursions to remote sites in support of specific mission science or operational objectives. An important consideration in rover design is ensuring that the habitation accommodations in the vehicle support these types of missions. No pressurized rovers have ever been used in human spaceflight, but several have been proposed. The current NASA pressurized rover reference configuration is based on the third generation of the prototype small pressurized rover initially developed under Constellation. Using the NASA reference configuration, habitability considerations are discussed in the context of a notional five-day science excursion. The primary focus will be on the time the crew spends in the cabin, as opposed to time spent outside the vehicle on science-based EVAs. On each day of the excursion, the specific crew activities will be detailed. Crew activities that will be assessed include post sleep, EVA preparation, daily planning conference, private medical conference, traverse driving, EVA cabin egress, EVA cabin ingress, post-EVA activity, crew meals, pre-egress site observation and analysis, crew exercise, pre-sleep, and sleep. Considerations for crew fatigue will be discussed, including lessons learned from field testing. Finally, the assessment will identify hypotheses to assess in future analog missions and suitable test campaigns to evaluate them.

Pressurized Rover↗

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

Dufrene, Warren R., Jr.↗

Science Activity Planner for the MER Mission

The Maestro Science Activity Planner is a computer program that assists human users in planning operations of the Mars Explorer Rover (MER) mission and visualizing scientific data returned from the MER rovers. Relative to its predecessors, this program is more powerful and easier to use. This program is built on the Java Eclipse open-source platform around a Web-browser-based user-interface paradigm to provide an intuitive user interface to Mars rovers and landers. This program affords a combination of advanced display and simulation capabilities. For example, a map view of terrain can be generated from images acquired by the High Resolution Imaging Science Explorer instrument aboard the Mars Reconnaissance Orbiter spacecraft and overlaid with images from a navigation camera (more precisely, a stereoscopic pair of cameras) aboard a rover, and an interactive, annotated rover traverse path can be incorporated into the overlay. It is also possible to construct an overhead perspective mosaic image of terrain from navigation-camera images. This program can be adapted to similar use on other outer-space missions and is potentially adaptable to numerous terrestrial applications involving analysis of data, operations of robots, and planning of such operations for acquisition of scientific data.

Norris, Jeffrey S.↗