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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.

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NASA NTRS2012

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.↗
NASA NTRS2004

Mars Exploration Rover Terminal Descent Mission Modeling and Simulation

Because of NASA's added reliance on simulation for successful interplanetary missions, the MER mission has developed a detailed EDL trajectory modeling and simulation. This paper summarizes how the MER EDL sequence of events are modeled, verification of the methods used, and the inputs. This simulation is built upon a multibody parachute trajectory simulation tool that has been developed in POST I1 that accurately simulates the trajectory of multiple vehicles in flight with interacting forces. In this model the parachute and the suspended bodies are treated as 6 Degree-of-Freedom (6 DOF) bodies. The terminal descent phase of the mission consists of several Entry, Descent, Landing (EDL) events, such as parachute deployment, heatshield separation, deployment of the lander from the backshell, deployment of the airbags, RAD firings, TIRS firings, etc. For an accurate, reliable simulation these events need to be modeled seamlessly and robustly so that the simulations will remain numerically stable during Monte-Carlo simulations. This paper also summarizes how the events have been modeled, the numerical issues, and modeling challenges.

Raiszadeh, Behzad↗
NASA NTRS1994

Motion Control of Rover-Mounted Manipulators

This paper presents a simple online approach for motion control of rover-mounted manipulators. An integrated kinetic model of the rover-plus-manipulator system is derived which incorporates the nonholonomic rover constraint with the holonomic end-effector constraint. The redundancy introduced by the rover mobility is exploited to perform a set of user-specified additional tasks during end-effector motion. The configuration control approach is utilized to satisfy the nonholonomic rover constraint, while accomplishing the end-effector motion and the redundancy resolution goal simultaneously. This framework allows the user to assign weighting factors to the rover movement and manipulator motion, as well as to each task specification. The computational efficiency of the control scheme makes it particularly suitable for real-time implementation. The proposed method is applied to a planar two-jointed arm mounted on a rover, and computer simulation results are presented for illustration.

robotics rover manipulator holonomic end-effector ↗
NASA NTRS2023

NASA's Center Innovation Fund (CIF) Internal Research and Development (IRAD) Handling Qualities Study on the Mikrolar Motion Platform Test Report

In order to support the National Aeronautics and Space Administration’s (NASA) Extravehicular Activity and Surface Mobility Program (EHP), system engineers, designers, and researchers embarked on a yearlong challenge to develop a new lunar rover-based motion table simulator to study handling qualities of lunar rovers in the lunar South Pole region, support development research for any lunar rover vendor, and provide a lunar training capability for future lunar/planetary astronauts. In 1989, the United Kingdom’s Royal Air Force Institute of Aviation Medicine (RAF-IAM) stated that motion platforms are the only simulation devices capable of fully stimulating the body motion sensors. They confirmed that motion platforms can impart accelerations to the whole body and therefore exercise the automatic motion feedback-loop that operators are used to. With both visual and motion cues handling the vehicle becomes more realistic. Strachan (2019) con-firms motion cueing from a well set-up motion platform has been found to be important especially in conditions such as night or reduced visibility where motion cues may be more relied upon

Motion Table↗
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 NTRS2013

Surface Telerobotics: Development and Testing of a Crew Controlled Planetary Rover System

During Summer 2013, we conducted a series of tests to examine how astronauts in the In- ternational Space Station (ISS) can remotely operate a planetary rover. The tests simulated portions of a proposed mission, in which an astronaut in lunar orbit remotely operates a planetary rover to deploy a radio telescope on the lunar farside. In this paper, we present the design, implementation, and preliminary test results.

Fong, Terry↗
NASA NTRS2014

Results from Testing Crew-Controlled Surface Telerobotics on the International Space Station

During Summer 2013, the Intelligent Robotics Group at NASA Ames Research Center conducted a series of tests to examine how astronauts in the International Space Station (ISS) can remotely operate a planetary rover. The tests simulated portions of a proposed lunar mission, in which an astronaut in lunar orbit would remotely operate a planetary rover to deploy a radio telescope on the lunar far side. Over the course of Expedition 36, three ISS astronauts remotely operated the NASA "K10" planetary rover in an analogue lunar terrain located at the NASA Ames Research Center in California. The astronauts used a "Space Station Computer" (crew laptop), a combination of supervisory control (command sequencing) and manual control (discrete commanding), and Ku-band data communications to command and monitor K10 for 11 hours. In this paper, we present and analyze test results, summarize user feedback, and describe directions for future research.

robotics↗
NASA NTRS1978

Procedures for the interpretation and use of elevation scanning laser/multi-sensor data for short range hazard detection and avoidance for an autonomous planetary rover

An autonomous roving science vehicle that relies on terrain data acquired by a hierarchy of sensors for navigation was one method of carrying out such a mission. The hierarchy of sensors included a short range sensor with sufficient resolution to detect every possible obstacle and with the ability to make fast and reliable terrain characterizations. A multilaser, multidetector triangulation system was proposed as a short range sensor. The general system was studied to determine its perception capabilities and limitations. A specific rover and low resolution sensor system was then considered. After studying the data obtained, a hazard detection algorithm was developed that accounts for all possible terrains given the sensor resolution. Computer simulation of the rover on various terrains was used to test the entire hazard detection system.

Troiani, N.↗
NASA NTRS1992

An EVACS simulation with nested transactions

Documented here is the recent effort of the MISSION Kernel Team on an Extra-Vehicular Activity Control System (EVACS) simulation with nested transactions. The team has implemented the EVACS simulation along with a design for nested transactions. The EVACS simulation is a project wide aid to exploring Mission and Safety Critical (MASC) applications and their support software. For this effort it served as a trial scenario for demonstrating nested transactions and exercising the transaction support design. The EVACS simulation is a simulation of some aspects of the Extra-Vehicular Activity Control System, in particular, just the selection of communication frequencies. Its current definition is quite narrow, serving only as a starting point for prototyping purposes. (EVACS itself may be supplanted in a larger scenario of a lunar outpost with astronauts and a lunar rover.) Initially the simulation of frequency selection was written without consideration of nested transactions. This scenario was then modified to embed its processing in nested transactions. To simplify the prototyping effort, only two aspects of the general design for transaction support have been implemented: the basic architecture and state recovery. The simulation has been implemented in the programming language Smalltalk. It consists of three components: (1) a simulation support code which provides the framework for initiating, interacting and tracing the system; (2) the EVACS application code itself, including its calls upon nested transaction support; and (3) a transaction support code which implements the logic necessary for nested transactions. Each of these components deserves further description, but for now only the transaction support is discussed.

Auty, David↗
NASA NTRS2011

NEEMO 14: Evaluation of Human Performance for Rover, Cargo Lander, Crew Lander, and Exploration Tasks in Simulated Partial Gravity

The ultimate success of future human space exploration missions is dependent on the ability to perform extravehicular activity (EVA) tasks effectively, efficiently, and safely, whether those tasks represent a nominal mode of operation or a contingency capability. To optimize EVA systems for the best human performance, it is critical to study the effects of varying key factors such as suit center of gravity (CG), suit mass, and gravity level. During the 2-week NASA Extreme Environment Mission Operations (NEEMO) 14 mission, four crewmembers performed a series of EVA tasks under different simulated EVA suit configurations and used full-scale mockups of a Space Exploration Vehicle (SEV) rover and lander. NEEMO is an underwater spaceflight analog that allows a true mission-like operational environment and uses buoyancy effects and added weight to simulate different gravity levels. Quantitative and qualitative data collected during NEEMO 14, as well as from spacesuit tests in parabolic flight and with overhead suspension, are being used to directly inform ongoing hardware and operations concept development of the SEV, exploration EVA systems, and future EVA suits. OBJECTIVE: To compare human performance across different weight and CG configurations. METHODS: Four subjects were weighed out to simulate reduced gravity and wore either a specially designed rig to allow adjustment of CG or a PLSS mockup. Subjects completed tasks including level ambulation, incline/decline ambulation, standing from the kneeling and prone position, picking up objects, shoveling, ladder climbing, incapacitated crewmember handling, and small and large payload transfer. Subjective compensation, exertion, task acceptability, and duration data as well as photo and video were collected. RESULTS: There appear to be interactions between CG, weight, and task. CGs nearest the subject s natural CG are the most predictable in terms of acceptable performance across tasks. Future research should focus on understanding the interactions between CG, mass, and subject differences.

Chappell, Steven P.↗
NASA NTRS1980

Interpretation of laser/multi-sensor data for short range terrain modeling and hazard detection

A terrain modeling algorithm that would reconstruct the sensed ground images formed by the triangulation scheme, and classify as unsafe any terrain feature that would pose a hazard to a roving vehicle is described. This modeler greatly reduces quantization errors inherent in a laser/sensing system through the use of a thinning algorithm. Dual filters are employed to separate terrain steps from the general landscape, simplifying the analysis of terrain features. A crosspath analysis is utilized to detect and avoid obstacles that would adversely affect the roll of the vehicle. Computer simulations of the rover on various terrains examine the performance of the modeler.

Messing, B. S.↗
NASA NTRS1991

Additions to Mars Global Reference Atmospheric Model (Mars-GRAM)

Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification has also been made which allows heights to go below local terrain height and return realistic pressure, density, and temperature (not the surface values) as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local valley areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch version of Mars-GRAM are presented.

Justus, C. G.↗
NASA NTRS1992

Additions to Mars Global Reference Atmospheric Model (MARS-GRAM)

Three major additions or modifications were made to the Mars Global Reference Atmospheric Model (Mars-GRAM): (1) in addition to the interactive version, a new batch version is available, which uses NAMELIST input, and is completely modular, so that the main driver program can easily be replaced by any calling program, such as a trajectory simulation program; (2) both the interactive and batch versions now have an option for treating local-scale dust storm effects, rather than just the global-scale dust storms in the original Mars-GRAM; and (3) the Zurek wave perturbation model was added, to simulate the effects of tidal perturbations, in addition to the random (mountain wave) perturbation model of the original Mars-GRAM. A minor modification was also made which allows heights to go 'below' local terrain height and return 'realistic' pressure, density, and temperature, and not the surface values, as returned by the original Mars-GRAM. This feature will allow simulations of Mars rover paths which might go into local 'valley' areas which lie below the average height of the present, rather coarse-resolution, terrain height data used by Mars-GRAM. Sample input and output of both the interactive and batch versions of Mars-GRAM are presented.

Justus, C. G.↗
NASA NTRS2004

Neural network tracking and extension of positive tracking periods

Feature detectors have been considered for the role of supplying additional information to a neural network tracker. The feature detector focuses on areas of the image with significant information. Basically, if a picture says a thousand words, the feature detectors are looking for the key phrases (keypoints). These keypoints are rotationally invariant and may be matched across frames. Application of these advanced feature detectors to the neural network tracking system at JPL has promising potential. As part of an ongoing program, an advanced feature detector was tested for augmentation of a neural network based tracker. The advance feature detector extended tracking periods in test sequences including aircraft tracking, rover tracking, and simulated Martian landing. Future directions of research are also discussed.

feature extraction↗
NASA NTRS2000

Field Experiments with Planetary Surface Rovers: Lessons for Mars Mission Architecture

Over the last decade, a variety of field experiments have been performed that simulate operations of a rover on Mars. These, in combination with the Pathfinder experience, lead to a realistic assessment of rover mission capabilities and to recommendations for rover technology and mission architecture to improve the science return of Mars exploration. A table summarizes field experiments that represent a range of possible mission designs and operational strategies. The experiments varied by the type and quality of imaging systems and other instrumentation, the use of orbital and aerial imaging and spectroscopy, the communcation bandwidth and command strategy, and the distance traveled. All mission simulations were blind field tests operated by science teams whose interpretations were compared to field ground truth providing an assessment of the accuracy of remote science interpretations and a better understanding of where improvements are needed.

Stoker, Carol↗