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NASA NTRS2016

Mars 2020 Entry, Descent and Landing Instrumentation 2 (MEDLI2)

The Mars Entry Descent and Landing Instrumentation 2 (MEDLI2) sensor suite will measure aerodynamic, aerothermodynamic, and TPS performance during the atmospheric entry, descent, and landing phases of the Mars 2020 mission. The key objectives are to reduce design margin and prediction uncertainties for the aerothermal environments and aerodynamic database. For MEDLI2, the sensors are installed on both the heatshield and backshell, and include 7 pressure transducers, 17 thermal plugs, and 3 heat flux sensors (including a radiometer). These sensors will expand the set of measurements collected by the highly successful MEDLI suite, collecting supersonic pressure measurements on the forebody, a pressure measurement on the aftbody, direct heat flux measurements on the aftbody, a radiative heating measurement on the aftbody, and multiple near-surface thermal measurements on the thermal protection system (TPS) materials on both the forebody and aftbody. To meet the science objectives, supersonic pressure transducers and heat flux sensors are currently being developed and their qualification and calibration plans are presented. Finally, the reconstruction targets for data accuracy are presented, along with the planned methodologies for achieving the targets.

Aerodynamics↗

NASA NTRS2019

Mars Reconnaissance Orbiter maneuver plan for Mars 2020 entry, descent, and landing support and beyond

The Mars Reconnaissance Orbiter (MRO) spacecraft continues to perform valuable science observations at Mars, provide telecommunication relay for surface assets, and characterize landing sites for future missions. MRO provided primary relay support for the InSight Mission during Entry, Descent, and Landing (EDL) on November26, 2018. This paper discusses the current maneuver plan to support Mars 2020 EDL and maintain MRO’s orbit for science operations through 2028.

Menon, Premkumar R.↗

NASA NTRSDate not supplied

Inverse Estimation of Mars 2020 Entry Aeroheating Environments Using MEDLI2 Flight Data

The Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite collected heating and pressure data during entry into Mars' atmosphere of the Mars 2020 Perseverance rover. MEDLI2 included thermocouples, heat flux sensors, and pressure transducers on both the heatshield and the backshell. This paper covers the inverse estimation of heatshield and backshell surface heating based on the MEDLI2 Instrumented Sensor Plugs (MISPs), a network of thermocouples embedded in thermal protection system plugs across the aeroshell. Monte Carlo analysis was conducted to assess the sensitivity of the surface heat rate and temperature to uncertainties in thermocouple depth and material properties such as density, specific heat capacity, and thermal conductivity. Data from each MISP was also used to estimate the local time of transition from laminar to turbulent flow at each plug location.

Hannah S Alpert↗

NASA NTRS2021

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↗

NASA NTRS2021

Mars 2020 Perseverance trajectory reconstruction and performance from launch through landing

The Mars 2020 (M2020) Mission carrying Perseverance, the most advanced rover ever sent to Mars, successfully launched on an Atlas V 541 (AV-088) launch vehicle from the Eastern Test Range (ETR) at Cape Canaveral Air Force Station (CCAFS) in Florida at 11:50:00 UTC (T-Zero time) on July 30, 2020. After some station reconfiguration, carrier/telemetry were locked at both Deep Space Network (DSN) Canberra and Goldstone stations. Perseverance entered the Martian atmosphere at 20:36:50 Spacecraft Event Time (SCET) UTC, and landed inside Jezero Crater at 20:43:49 SCET UTC on February 18, 2021. Confirmation of nominal landing was received at the DSN Goldstone and Madrid tracking stations via the Mars Reconnaissance Orbiter at 20:55:11 Earth Received Time (ERT) UTC. This paper summarizes in detail the actual vs. predicted performance in terms of launch vehicle events, launch vehicle injection performance, actual DSN spacecraft lockup, trajectory correction maneuver performance, Entry, Descent, and Landing events, and overall trajectory and geometric characteristics.

Abilleira, Fernando↗

NASA NTRS2021

Mars 2020 Perseverance Trajectory Reconstruction and Performance from Launch through Landing

Wong, Mau↗

NASA NTRS2017

Prototyping an Onboard Scheduler for the Mars 2020 Rover

Efficiently operating a rover on the surface of Mars is challenging. Two factors combine to make this job particularly difficult: 1) communication opportunities are limited, 2) certain aspects of rover performance are difficult to predict. With limited communications, the rover must be given instructions on what to do for one or more Martian days at a time. In addition, the duration of many rover activities can be hard to predict, which leads to unpredictable energy use. Traditionally, conservatism is used to keep the rover safe and healthy. This approach, however can lead to a measurable loss in rover productivity. To regain some of this productivity, the Mars 2020 mission is prototyping the use of onboard scheduling software. The primary objective of this software is to identify and utilize opportunities that arise when actual rover performance is more efficient than the original, conservative prediction.

Benowitz, Ed↗

NASA NTRS2021

Analysis of Mars 2020 Perseverance Entry, Descent, and Landing Attitude Initialization Performance

The Mars 2020 Perseverance rover successfully landed at Jezero Crater on February 18, 2021. To perform this feat, the entry, descent, and landing navigation filter must be initialized with an estimate of the spacecraft state, which includes attitude from the cruise attitude control subsystem. Accuracy of this initial attitude estimate has an impact on important metrics such as touchdown velocity. This paper presents a post-landing reconstruction of the attitude initialization error budget, showing that the requirement of 0.15 deg ($3\sigma$, per axis) was met. Each error source is described and analyzed, including flight telemetry where possible. Analysis of the error budget shows that it is driven by systematic sun sensor errors, star-scanner-to-sun-sensor alignment stability, and inertial-measurement-unit-to-sun-sensor alignment stability. Finally, a contingency plan to initialize the navigation filter in the event of a star scanner failure is presented. While this plan was not needed in flight, results indicate that the attitude initialization requirement could have still been met in this off-nominal scenario.

Lo, Kevin D.↗

NASA NTRS2022

Sampling of Jezero Crater Máaz Formation By Mars 2020 Perseverance Rover

Collection of samples that could be returned to Earth from the floor of Jezero crater is a major goal of the Mars 2020 mission. Laboratory analyses of these will expand exploration of Jezero, a Noachian crater on Mars characterized by a delta–lake system with high potential for habitability. The samples will also be used to test current ideas about the early planetary evolution of Mars. The Perseverance rover has collected samples from two members of the Máaz formation, mapped in orbital images as the Crater floor fractured rough unit by [1]. Type localities of the Roubion and Rochette members have been targeted and abraded prior to sample collection. Here we summarize these sampling activities and the potential of sampling the Chal member of Máaz. A similar summary for samples collected from the Séítah formation is described in Hickman-Lewis et al. (this meeting).

Mars 2020↗

NASA NTRS2020

A ROS-based Simulator for Testing the Enhanced Autonomous Navigation of the Mars 2020 Rover

In order to achieve the ambitious objectives of the Mars 2020 (M2020) mission, in particular the ability to autonomously traverse more challenging terrains more efficiently, new surface mobility software was developed for Enhanced Navigation (ENav). That decision was made early in the project, before most of the new surface flight software (FSW) existed, which created a need for a separate framework where the new navigation algorithms could be quickly prototyped and tested, before more realistic FSW-based testbeds became available. The JPL robotics team chose the Robot Operating System [1] (ROS) as the environment in which to test the new ENav algorithms. This made it possible to write the algorithms in the C language required by the FSW, so they could be directly ported over to the flight module later on, while leveraging all the C++ libraries and tools provided by ROS for simulation and testing. The ENav algorithms were developed as a separate C library, and stubs were used to replace any FSW-specific code, such as Event Reporting (EVRs) and data products (DPs). A ROS simulator was developed to generate a rich set of varied 3D terrains representative of the candidate Mars landing sites and simulate the physics of the rover motion, the point cloud perceived by the rover’s stereo vision system, and the new thinking-while-driving (TWD) navigation logic which directs the rover to drive autonomously to user-specified waypoints. To simulate the rover motion and perception, a ROS node was developed that uses a software library called HyperDrive Sim (HDSim), which is a wrapper for the Rover Sequencing and Visualization Program [2] (RSVP). That library provides roverterrain settling, realistic slip modelling, and camera rendering capability based on the rover’s NavCam machine vision models. To simulate the navigation logic, a ROS node was created that initializes and runs the ENav algorithms in a way that mimics the FSW execution, while also providing the capability to load and replay data products, including re-running the recorded inputs through the ENav algorithms for testing. An engineering Graphical User Interface (GUI) was also developed to visualize various elements, such as the rover pose during the drive, the simulated and perceived terrain, the selected local and global paths to the goal, the evaluated candidate paths and the reasons why they were rejected, the keep-in and keep-out zones (KIOZs), etc. Finally, an advanced Monte Carlo (MC) framework that can run many simulations in parallel on the Cloud and automatically generate reports that capture the key ENav performance metrics was developed to evaluate the system in a statisticallymeaningful way. This paper provides an overview of the ROSbased simulator used for testing the M2020 ENav algorithms.

Toupet, Olivier↗

NASA NTRS2022

Balancing Predictive and Reactive Science Planning for Mars 2020 Perseverance

The design of the science planning process for a space science mission needs to find a balance between operational and resource constraints and scientific decision-making. Science planning has previously been characterized as either predictive or reactive. Predictive science planning is needed when constraints drive science activities to be planned far in advance. For example, a combination of long one-way light time plus high-stakes science decisions drove the Cassini-Huygens mission to Saturn to have an extremely predictive planning process. On the other extreme, reactive science planning is needed when constraints drive science activities to be planned based on the results of the previous plan. For example, the Mars Exploration Rover mission interacted with the surface of Mars, and so the planning team needed to know the state of the rover at the end of each planning cycle before starting the next cycle. Operational and resource constraints that require management on intermediate timescales has led to the development of a science planning process between these two extremes. For example, the Mars Science Laboratory is a technically complex rover and has a parallel predictive process that allows the operations team to manage engineering constraints several days in advance while maintaining the reactive tactical planning process similar to that of MER. The Mars 2020 Perseverance rover is a technically complex rover in the MSL style, but has an added layer of science complexity: it is tasked with collecting a returnable cache of scientifically valuable samples of Mars within prime mission. Thus, the science planning process also needs to accommodate high-stakes longer-term science decisions in the style of Cassini. In order to balance the push-pull of these constraints, we have developed a science campaign-focused operational paradigm for Mars 2020 Perseverance that allows for both predictive planning to accommodate technological complexity and high-stakes science decisions as well as reactive planning to accommodate the realities of interacting with the martian surface. This paradigm influenced the design of operational processes and operational tools.

Spanovich, Nicole↗

NASA NTRS2022

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↗

NASA NTRS2020

Using Explainable Scheduling for the Mars 2020 Rover Mission

Understanding the reasoning behind the behavior of an auto- mated scheduling system is essential to ensure that it will be trusted and consequently used to its full capabilities in critical applications. In cases where a scheduler schedules activities in an invalid location, it is usually easy for the user to infer the missing constraint by inspecting the schedule with the in- valid activity to determine the missing constraint. If a sched- uler fails to schedule activities because constraints could not be satisfied, determining the cause can be more challenging. In such cases it is important to understand which constraints caused the activities to fail to be scheduled and how to al- ter constraints to achieve the desired schedule. In this pa- per, we describe such a scheduling system for NASA’s Mars 2020 Perseverance Rover, as well as Crosscheck, an explain- able scheduling tool that explains the scheduler behavior. The scheduling system and Crosscheck are the baseline for oper- ational use to schedule activities for the Mars 2020 rover. As we describe, the scheduler generates a schedule given a set of activities and their constraints and Crosscheck: (1) provides a visual representation of the generated schedule; (2) analyzes and explains why activities failed to schedule given the con- straints provided; and (3) provides guidance on potential con- straint relaxations to enable the activities to schedule in future scheduler runs.

Chien, Steve↗

NASA NTRS2017

Mars 2020 Site-Specific Mission Performance Analysis: Part 2. Surface Traversability

The Mars 2020 Rover Mission (M2020) is characterized by long-range traverses between scientific Regions Of Interest (ROIs), as well as the demanding requirement on the distance and time for the inter-ROI traverses. As a result, surface traversability is one of the major driving factors for the landing site selection of M2020. With the newly developed Mars Terrain Traversability analysis Tools (MTTT), we performed traversability analysis of the eight candidate landing sites with an unprecedented granularity. This paper describes the MTTT analysis capabilities, as well as how the MTTT capabilities were used to down-select from eight to three candidate landing sites for further evaluation.

Milkovich, Sarah↗

NASA NTRS2025

Diverse and Highly Differentiated Lava Suite in Jezero Crater, Mars: Constraints on Intracrustal Magmatism Revealed By Mars 2020 PIXL

The Jezero crater floor features a suite of related, iron-rich lavas that were examined and sampled by the Mars 2020 rover Perseverance , and whose textures, minerals, and compositions were characterized by the Planetary Instrument for X-ray Lithochemistry (PIXL). This suite, known as the Máaz formation (fm), includes dark-toned basaltic/trachy-basaltic rocks with intergrown pyroxene, plagioclase feldspar, and altered olivine and overlying trachy-andesitic lava with reversely zoned plagioclase phenocrysts in a K-rich groundmass. Feldspar thermal disequilibrium textures indicate that they were carried from their crustal staging area. Bulk and mafic minerals have very high FeO and low MgO to FeO total ratios, which are partially reproduced by thermodynamic models involving high-degree fractional crystallization of a gabbroic assemblage and possibly also assimilation of iron-rich basement. Together, these in situ constraints on petrogenesis provide a uniquely detailed record of intracrustal processes beneath Jezero crater during a time period not represented by Mars samples to date.

Jezero Crater floor↗

NASA NTRS2019

Laboratory-Based Thermal Shock Investigation of Heat Flux Sensors for the Mars 2020 Backshell

In 2012 during the entry, descent, and landing of the Mars Science Laboratory (MSL), the MSL Entry, Descent, and Landing Instrumentation (MEDLI) sensor suite was collecting in-flight heatshield pressure and temperature data. The data collected by the MEDLI instruments has since been used for reconstruction of vehicle aerodynamics, atmospheric conditions, aerothermal heating, and Thermal Protection System (TPS) performance as well as material response model validation and refinement. The Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite for the Mars 2020 heatshield and backshell is being designed to expand on the measurements and knowledge gained from MEDLI. Similar to MEDLI, MEDLI2 will measure the pressure and temperature of the heatshield. MEDLI2 will additionally measure the temperature, pressure, total heat flux, and radiative heat flux on the backshell. Since the backshell instrumentation is new to MEDLI2, Do No Harm (DNH) testing was conducted on instrumented backshell TPS (SLA-561V) panels. The panels consisted of four pressure port holes, one Mars Entry Atmospheric Data System (MEADS) pressure port plug, one MEDLI2 Integrated Sensor Plug (MISP) thermal plug, and one heat flux sensor. DNH testing was conducted to ensure the performance of the TPS was not degraded due to sensor integration and to characterize any TPS performance changes. The testing consisted of environmental testing— vibration, shock, thermal vacuum (TVAC) cycling— and bounding aerothermal (arc jet) testing.

Miller, R. A.↗

NASA NTRS2019

Mars 2020 sample caching system contamination: how to clean hardware and keep it clean

The Mars 2020 Rover will have the capability to collect and cache samples for potential Mars sample return. Specifically, the sample caching system (SCS) is designed for coring Mars samples and acquiring regolith samples as well as handling, sealing and caching on Mars. As the potential first Martian samples that could be returned to Earth, assuring low levels of terrestrial contamination is of the utmost concern. In developing the SCS, the project prioritizes limiting sample contamination in organic, inorganic and biological areas. The focus of this paper is on the strategies being implemented to clean the assemble the sampling hardware to meet and maintain stringent contamination requirements.

Rainen, Richard↗

NASA NTRS2014

In-situ Geochronology on the Mars 2020 Rover with KArLE (The Potassium-Argon Laser Experiment)

A successful Mars exploration program has revealed chapters of Mars history, but in this book, the pages are ripped out of the binding and scattered across the surface. An examination of each page reveals interesting information, but there is no way to read the book in a logical order. Geochronology is the tool that puts page number onto the individual pages, and allows the book of Martian history to be read in its proper order. The KArLE experiment performs the first dedicated in situ geochronology investigation on Mars, bringing clarity to Mars 2020 samples and context to its landing site.

Cohen, Barbara A.↗