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MAPGEN: Mixed-Initiative Activity Planning for the Mars Exploration Rover Mission

This document describes the Mixed initiative Activity Plan Generation system MAPGEN. This system is one of the critical tools in the Mars Exploration Rover mission surface operations, where it is used to build activity plans for each of the rovers, each Martian day. The MAPGEN system combines an existing tool for activity plan editing and resource modeling, with an advanced constraint-based reasoning and planning framework. The constraint-based planning component provides active constraint and rule enforcement, automated planning capabilities, and a variety of tools and functions that are useful for building activity plans in an interactive fashion. In this demonstration, we will show the capabilities of the system and demonstrate how the system has been used in actual Mars rover operations. In contrast to the demonstration given at ICAPS 03, significant improvement have been made to the system. These include various additional capabilities that are based on automated reasoning and planning techniques, as well as a new Constraint Editor support tool. The Constraint Editor (CE) as part of the process for generating these command loads, the MAPGEN tool provides engineers and scientists an intelligent activity planning tool that allows them to more effectively generate complex plans that maximize the science return each day. The key to the effectiveness of the MAPGEN tool is an underlying constraint-based planning and reasoning engine.

Ai-Chang, Mitchell↗

Thermal Operability Improvements for the Mars 2020 Rover Surface Mission

The Mars 2020 Rover is scheduled to land on Mars on February 18, 2021. One of the primary mission objectives for the Mars 2020 Rover is to perform in-situ science and collect a set of Martian regolith samples for possible future return to Earth. In order to meet mission requirements, 20 samples must be collected, assessed, and sealed during the prime mission (1.5 Martian years, approximately 1000 Sols). This requires that the Mars 2020 Rover operate in a much more efficient and autonomous manner than its predecessor, the Mars Science Laboratory (MSL) Rover, Curiosity. The thermal designs of both Curiosity and the Mars 2020 Rover utilize warmup heaters to bring the actuators and cameras, located on the outside of the vehicle, up to their operating temperatures prior to use. These heaters consume energy during the mission. The Rover energy balance, between energy production and consumption, must be maintained in order to keep the mission moving safely forward. Increased efficiency in the way this warmup heater energy is allocated and used in the Mars 2020 Rover operations plan will result in more energy available for science and engineering activities. This paper discusses the improvements that were made in both hardware and software to improve the way the Mars 2020 Rover will operate thermally on Mars.

Lee, Chern-Jiin↗

Viper Science Operations: Lunar Dynamic Science Table and ‘Tracker’ Tool.

Introduction: The NASA VIPER lunar rover mission [1] presents a unique operational paradigm within the history of robotic spaceflight. The proximity of the Moon to the Earth and the terrain elements (surface characteristics, light/shadow dynamics, communication links) of the Lunar South Polar landing site create unprecedented operational conditions between these two planetary bodies. Apollo era lunar science and exploration included humans in situ to operate instruments and assimilate observational inputs in real-time. Previous lunar orbital missions have worked to operational timescales, e.g., decisional timelines and communication exchanges, that were weeks in duration. Mars rover missions have worked to operational timescales, e.g., decisional timelines and communication exchanges between Mars and Earth, that were hours, days, and weeks in length. In the case of the VIPER mission, our operational decisioning for rover driving and instrument commanding will be compressed to minute-scale timeframes. These operational conditions will directly impact the workflow and speed with which the VIPER Science Team (VST) will be required to synthesize and analyze data and produce timely science-driven decisions throughout surface mission operations [2]. The VST in the VIPER Mission Science Center (MSC) and the Mission Operations Center (MOC) shall provide mission-enhancing scientific input to guide traverse planning and drill site confirmation/selection throughout surface operations. Further, the VST input will be of vital importance to the mission’s ability to maximize science return and to meet broader NASA objectives for future lunar ISRU and exploration activities. Specifically, the VST in the MSC and MOC will provide science-driven, consensus-based, timely input and decision-making to enhance mission operations and align mission science return with broader Agency goals. They will enable the characterization of the distribution (lateral and vertical extent, concentration, variability), form (chemical/physical state of these reservoirs of lunar water and key isotopes), and context (e.g., accessibility/overburden, environment, soil mechanics, trafficability, and temperatures) of lunar polar volatiles and water content for the VIPER mission. Additionally, the MSC will be selecting or reconfirming the location and path towards and from the third drill site (Drill Site Charlie) within each Science Station [6]. To enable scientific decision-making within the operational paradigm of the VIPER lunar rover mission requires detailed articulation of the VST’s scientific objectives and goals, and the operationalization of these objectives and goals through their association with specific data products, tasks, and decisional procedures. Further, defining and tracking scientific success metrics throughout surface operations will enable the VST to have a quantified understanding of the mission’s evolving ability to accomplish the stated scientific objectives and goals both during and after the mission. This abstract provides an overview of the methods and development activities towards defining, operationalizing, and tracking scientific objectives and goals throughout VIPER surface operations. Specifically, we focus on the VIPER Lunar Dynamic Science Table (LDST) and the VIPER “Tracker” tool.

Darlene Sze Shien Lim↗

Modeling and Simulation for Mission Operations Work System Design

Work System analysis and design is complex and non-deterministic. In this paper we describe Brahms, a multiagent modeling and simulation environment for designing complex interactions in human-machine systems. Brahms was originally conceived as a business process design tool that simulates work practices, including social systems of work. We describe our modeling and simulation method for mission operations work systems design, based on a research case study in which we used Brahms to design mission operations for a proposed discovery mission to the Moon. We then describe the results of an actual method application project-the Brahms Mars Exploration Rover. Space mission operations are similar to operations of traditional organizations; we show that the application of Brahms for space mission operations design is relevant and transferable to other types of business processes in organizations.

Sierhuis, Maarten↗

Unmanned surface traverses of Mars and Moon: Science objectives, payloads, operations

Science objectives and properties to be measured are outlined for long surface traverse missions on Mars and the Moon, with remotely-controlled roving vehicles. A series of candidate rover payloads is proposed for each planet, varying in weight, cost, purpose, and development needed. The smallest weighs 35 kg; the largest almost 300 kg. A high degree of internal control will be needed on the Mars rover, including the ability to carry out complex science sequences. Decision-making by humans in the Mars mission includes supervisory control of rover operations and selection of features and samples of geological and biological interest. For the lunar mission, less control on the rover and more on earth is appropriate. Science portions of the rover mission profile are outlined, with timelines and mileage breakdowns. Operational problem areas for Mars include control, communications, data storage, night operations, and the mission operations system. For the moon, science data storage on the rover would be unnecessary and control much simpler.

Jaffe, L. D.↗

Ground-based Automated Scheduling for Operations of the Mars 2020 Rover Mission

The National Aeronautics and Space Administration’s (NASA) Mars 2020 Rover, named Perseverance, landed on the surface of Mars in Jezero Crater on February 18, 2021. Since the landing, the rover’s activities have been planned with the aid of a ground-based automated scheduling system called Copilot. Automated scheduling is very rare for planetary rover missions. Historically humans have created a schedule manually and ensured that the schedule satisfied all constraints. Higher levels of automation in the system allows science planners to produce schedules for the rover more quickly. In addition to scheduling user-provided activities, Copilot generates and schedules two types of support activities: sleep activities and heating activities. Some activities require the CPU to be on as they execute, so Copilot schedules wakeups and shutdowns of the CPU at the appropriate times. Some activities require areas of the rover to be heated before they can execute, and that heating must be maintained throughout the duration of the activity. Copilot schedules the preheat and maintenance heating activities for the user-provided activities that require them. To facilitate Copilot usage, the Crosscheck tool shows the science planners how Copilot constructed a schedule. For activities that fail to be scheduled, Crosscheck gives information on the constraints that the activity would have violated. This gives the users insight into how to change the input activities and constraints in order to achieve a schedule that satisfies their goals.

Towey, Shannon↗

Martian and lunar science with remotely-controlled long-range surface vehicles

Science objectives are outlined for long surface traverse missions on Mars and the moon, with remotely-controlled roving vehicles. Series of candidate rover science payloads are proposed, varying in purpose, development needed, cost, and weight (35 to almost 300 kg). A high degree of internal control will be needed on the Mars rover, including the ability to carry out complex science sequences. Decision-making by humans in the Mars mission includes supervisory control of rover operations and selection of features and samples of geological and biological interest. For the lunar mission, less control on the rover and more on earth is appropriate. Operational problem areas for Mars include control, communications, data storage, night operations, and the mission operations system. For the moon, science data storage on the rover would be unnecessary and control much simpler.

Jaffe, L. D.↗

Implementing Distributed Operations: A Comparison of Two Deep Space Missions

Two very different deep space exploration missions--Mars Exploration Rover and Cassini--have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a mission of more than ten years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process. Additionally, MER has benefited from the initial co-location of its entire operations team, and from having a single Principal Investigator, while Cassini operations have had to reconcile multiple science teams distributed from before launch. Cassini has faced greater challenges in implementing effective distributed operations. Because extensive early planning is required to capture science opportunities on its tour and because sequence development takes significantly longer than sequence execution, multiple teams are contributing to multiple sequences concurrently. The complexity of integrating inputs from multiple teams is exacerbated by spacecraft operability issues and resource contention among the teams, each of which has their own Principal Investigator. Finally, much of the technology that MER has exploited to facilitate distributed operations was not available when the Cassini ground system was designed, although later adoption of web-based and telecommunication tools has been critical to the success of Cassini operations.

Cassini Mission↗

Implementing distributed operations : a comparison of two Deep Space Missions

Two very different deep space exploration missions—Mars Exploration Rover and Cassini—have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a prime mission of four years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process.

Larsen, Barbara↗

Mars mission science operations facilities design

A variety of designs for Mars rover and lander science operations centers are discussed in this paper, beginning with a brief description of the Pathfinder science operations facility and its strengths and limitations. Particular attention is then paid to lessons learned in the design and use of operations facilities for a series of mission-like field tests of the FIDO prototype Mars rover. These lessons are then applied to a proposed science operations facilities design for the 2003 Mars Exploration Rover (MER) mission. Issues discussed include equipment selection, facilities layout, collaborative interfaces, scalability, and dual-purpose environments. The paper concludes with a discussion of advanced concepts for future mission operations centers, including collaborative immersive interfaces and distributed operations. This paper's intended audience includes operations facility and situation room designers and the users of these environments.

Ground Data System (GDC)↗

Horizon Detection for Mars Surface Operations

A new image processing method for automated horizon detection is presented in this paper. This method was developed for the Mars Exploration Rovers mission’s surface operations to aid in determining orbiter visibility periods for downlink data, and is now being considered for all Mars surface missions and for a variety of applications. Starting with images received from Mars rovers or landers, the horizon pixel location is found by (1) obtaining the gradient images using the Sobel operator, (2) calculating the preliminary horizon locations by optimizing the maximum difference between sky and ground regions in the gradient domain, and (3) applying a multi-variable thresholding method. The results are analyzed using a variety of images from the Mars rovers, as an example one dataset’s results were categorized as 94.2% Good, 4.11% Okay, and 1.65% Poor. The pixel location corresponding to the found horizon in an image is converted to azimuth and elevation values using the camera model. The elevation of the terrain surrounding the rover or lander directly affects the duration orbiters are visible for downlink data volume, and when the sun is visible for image quality or solar energy consumption. Having an automated process to detect the elevation of the terrain allows the operation team to better predict the outcome of the plan, reducing heath and safety risks and allowing new operational limits to be defined.

Oij, Stephanie Lynn↗

Viking '79 Rover study. Volume 1: Summary report

The results of a study to define a roving vehicle suitable for inclusion in a 1979 Viking mission to Mars are presented. The study focused exclusively on the 1979 mission incorporating a rover that would be stowed on and deployed from a modified Viking lander. The overall objective of the study was to define a baseline rover, the lander/rover interfaces, a mission operations concept, and a rover development program compatible with the 1979 launch opportunity. During the study, numerous options at the rover system and subsystem levels were examined and a baseline configuration was selected. Launch vehicle, orbiter, and lander performance capabilities were examined to ensure that the baseline rover could be transported to Mars using minimum-modified Viking '75 hardware and designs.

Source record↗

From Prime to Extended Mission: Evolution of the MER Tactical Uplink Process

To support a 90-day surface mission for two robotic rovers, the Mars Exploration Rover mission designed and implemented an intensive tactical operations process, enabling daily commanding of each rover. Using a combination of new processes, custom software tools, a Mars-time staffing schedule, and seven-day-a-week operations, the MER team was able to compress the traditional weeks-long command-turnaround for a deep space robotic mission to about 18 hours. However, the pace of this process was never intended to be continued indefinitely. Even before the end of the three-month prime mission, MER operations began evolving towards greater sustainability. A combination of continued software tool development, increasing team experience, and availability of reusable sequences first reduced the mean process duration to approximately 11 hours. The number of workshifts required to perform the process dropped, and the team returned to a modified 'Earth-time' schedule. Additional process and tool adaptation eventually provided the option of planning multiple Martian days of activity within a single workshift, making 5-day-a-week operations possible. The vast majority of the science team returned to their home institutions, continuing to participate fully in the tactical operations process remotely. MER has continued to operate for over two Earth-years as many of its key personnel have moved on to other projects, the operations team and budget have shrunk, and the rovers have begun to exhibit symptoms of aging.

mission operations↗

Mars Science Laboratory Rover System Thermal Test

On November 26, 2011, NASA launched a large (900 kg) rover as part of the Mars Science Laboratory (MSL) mission to Mars. The MSL rover is scheduled to land on Mars on August 5, 2012. Prior to launch, the Rover was successfully operated in simulated mission extreme environments during a 16-day long Rover System Thermal Test (STT). This paper describes the MSL Rover STT, test planning, test execution, test results, thermal model correlation and flight predictions. The rover was tested in the JPL 25-Foot Diameter Space Simulator Facility at the Jet Propulsion Laboratory (JPL). The Rover operated in simulated Cruise (vacuum) and Mars Surface environments (8 Torr nitrogen gas) with mission extreme hot and cold boundary conditions. A Xenon lamp solar simulator was used to impose simulated solar loads on the rover during a bounding hot case and during a simulated Mars diurnal test case. All thermal hardware was exercised and performed nominally. The Rover Heat Rejection System, a liquid-phase fluid loop used to transport heat in and out of the electronics boxes inside the rover chassis, performed better than predicted. Steady state and transient data were collected to allow correlation of analytical thermal models. These thermal models were subsequently used to predict rover thermal performance for the MSL Gale Crater landing site. Models predict that critical hardware temperatures will be maintained within allowable flight limits over the entire 669 Sol surface mission.

Novak, Keith S.↗

Mars Science Laboratory Rover System Thermal Test

On November 26, 2011, NASA launched a large (900 kg) rover as part of the Mars Science Laboratory (MSL) mission to Mars. The MSL rover is scheduled to land on Mars on August 5, 2012. Prior to launch, the Rover was successfully operated in simulated mission extreme environments during a 16-day long Rover System Thermal Test (STT). This paper describes the MSL Rover STT, test planning, test execution, test results, thermal model correlation and flight predictions. The rover was tested in the JPL 25-Foot Diameter Space Simulator Facility at the Jet Propulsion Laboratory (JPL). The Rover operated in simulated Cruise (vacuum) and Mars Surface environments (8 Torr nitrogen gas) with mission extreme hot and cold boundary conditions. A Xenon lamp solar simulator was used to impose simulated solar loads on the rover during a bounding hot case and during a simulated Mars diurnal test case. All thermal hardware was exercised and performed nominally. The Rover Heat Rejection System, a liquid-phase fluid loop used to transport heat in and out of the electronics boxes inside the rover chassis, performed better than predicted. Steady state and transient data were collected to allow correlation of analytical thermal models. These thermal models were subsequently used to predict rover thermal performance for the MSL Gale Crater landing site. Models predict that critical hardware temperatures will be maintained within allowable flight limits over the entire 669 Sol surface mission.

Novak, Keith S.↗

Constellation Architecture Team-Lunar: Lunar Habitat Concepts

This paper will describe lunar habitat concepts that were defined as part of the Constellation Architecture Team-Lunar (CxAT-Lunar) in support of the Vision for Space Exploration. There are many challenges to designing lunar habitats such as mission objectives, launch packaging, lander capability, and risks. Surface habitats are required in support of sustaining human life to meet the mission objectives of lunar exploration, operations, and sustainability. Lunar surface operations consist of crew operations, mission operations, EVA operations, science operations, and logistics operations. Habitats are crewed pressurized vessels that include surface mission operations, science laboratories, living support capabilities, EVA support, logistics, and maintenance facilities. The challenge is to deliver, unload, and deploy self-contained habitats and laboratories to the lunar surface. The CxAT-Lunar surface campaign analysis focused on three primary trade sets of analysis. Trade set one (TS1) investigated sustaining a crew of four for six months with full outpost capability and the ability to perform long surface mission excursions using large mobility systems. Two basic habitat concepts of a hard metallic horizontal cylinder and a larger inflatable torus concept were investigated as options in response to the surface exploration architecture campaign analysis. Figure 1 and 2 depicts the notional outpost configurations for this trade set. Trade set two (TS2) investigated a mobile architecture approach with the campaign focused on early exploration using two small pressurized rovers and a mobile logistics support capability. This exploration concept will not be described in this paper. Trade set three (TS3) investigated delivery of a "core' habitation capability in support of an early outpost that would mature into the TS1 full outpost capability. Three core habitat concepts were defined for this campaign analysis. One with a four port core habitat, another with a 2 port core habitat, and the third investigated leveraging commonality of the lander ascent module and airlock pressure vessel hard shell. The paper will describe an overview of the various habitat concepts and their functionality. The Crew Operations area includes basic crew accommodations such as sleeping, eating, hygiene and stowage. The EVA Operations area includes additional EVA capability beyond the suit-port airlock function such as redundant airlock(s), suit maintenance, spares stowage, and suit stowage. The Logistics Operations area includes the enhanced accommodations for 180 days such as closed loop life support systems hardware, consumable stowage, spares stowage, interconnection to the other Hab units, and a common interface mechanism for future growth and mating to a pressurized rover. The Mission & Science Operations area includes enhanced outpost autonomy such as an IVA glove box, life support, and medical operations.

Toups, Larry↗