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NASA NTRS1991

3-D laser radar simulation for autonomous spacecraft landing

A sophisticated 3D laser radar sensor simulation, developed and applied to the task of autonomous hazard detection and avoidance, is presented. This simulation includes a backward ray trace to sensor subpixels, incoherent subpixel integration, range dependent noise, sensor point spread function effects, digitization noise, and AM-CW modulation. Specific sensor parameters, spacecraft lander trajectory, and terrain type have been selected to generate simulated sensor data.

Reiley, Michael F.↗

NASA NTRS2005

Small Dog-Like Quadruped Robot Powered With McKibben Air Muscles

Planetary surface robotic exploration is typically done by wheeled robots, which are limited to traveling on relatively flat terrain. The goal of this project was to design a bio-inspired robot to mimic the movements and agility of animals to navigate in various types of natural terrain, such as found on Mars. My objective for the summer was to design and construct a quadruped robot with a locomotion gait similar to a small dog. The design includes four legs and an actuated flexible spine for added mobility and performance; each leg has three joints - hip, knee, and ankle. I created 3D CAD models and machined the pieces for the assemblies of each part. One of the key areas of concern is weight vs. power issues for the driving force of locomotion. To maximize the power-to-weight ratio, I used McKibben air muscles to drive the motion of the quadruped. The prototype went through several iterations to analyze performance, with adjustments made to each assembly. We expect the final working prototype will be capable of standing unassisted and pronking into the air without active control. It will serve as a research platform for future bio-inspired control algorithms.

Lacy, John M.↗

NASA NTRS2021

Machine Vision based Sample-Tube Localization for Mars Sample Return

A potential Mars Sample Return (MSR) architecture is being jointly studied by NASA and ESA. As currently envisioned, the MSR campaign consists of a series of 3 missions: sample cache, fetch and return to Earth. In this paper, we focus on the fetch part of the MSR, and more specifically the problem of autonomously detecting and localizing sample tubes deposited on the Martian surface. Towards this end, we study two machine-vision based approaches: First, a geometrydriven approach based on template matching that uses hardcoded filters and a 3D shape model of the tube; and second, a data-driven approach based on convolutional neural networks (CNNs) and learned features. Furthermore, we present a large benchmark dataset of sample-tube images, collected in representative outdoor environments and annotated with ground truth segmentation masks and locations. The dataset was acquired systematically across different terrain, illumination conditions and dust-coverage; and benchmarking was performed to study the feasibility of each approach, their relative strengths and weaknesses, and robustness in the presence of adverse environmental conditions.

Detry, R.↗

NASA NTRSDate not supplied

Initial Testing Results and Forward Design Considerations for the Tri-Rotor Hand Controller

The Lunar Terrain Vehicle (LTV) is one of the key elements of NASA’s Artemis return to the Moon. As an unpressurized rover, the LTV hand controller must take into account the limitations of the spacesuit worn by the crew as well as lessons learned operating the Apollo Lunar Roving Vehicle and preliminary NASA simulations. Because the NASA Ground Test Unit (GTU) design features omnidirectional steering, NASA engineers developed the TriRotor is an innovation to minimize crew fatigue and discomfort. NASA conducted a series of tests, initially with 3D printed mockup controllers, and expanding to a functional prototype used in an LTV video wall simulation. The Tri-Rotor compared favorably with legacy Apollo T-Handles, though numerous test subject comments were collected to improve the controller’s usability. Several options to improve the Tri-Rotor’s usability are also discussed, along with opportunities to test the Tri-Rotor in Virtual Reality, a motion table, and in field analogs.

Hand Controller↗

NASA NTRS2024

GCAS Visualization Codebase Augmentation Migration to Modern Standards and Feature Enhancements

The Glenn Research Center Communication Analysis Suite (GCAS) includes many analysis tools that can be used to support a wide range of scenarios. It includes a visualization tool that implements the three.js graphics library to display a three-dimensional (3D) representation of its results. This software will enable researchers, engineers, and mission planners to interact intuitively with and understand the results of their analyses, which might not be apparent from raw data. With NASA’s efforts to return humans to the Moon as a part of the Artemis missions, the GCAS has been used extensively for lunar terrain and landing system development analysis, which is vital to ensuring mission achievability and safety. This has created the need to add several significant features to the visualization tool, such as the ability to display the terrain of the lunar surface accurately and to provide information demonstrating how a given region might impact mission objectives. Many of the changes made to the visualization tool can be separated into one of three general advancements: code restructuring to adhere to modern coding standards and practices, new user camera controls for first-person and third-person perspective views, and a terrain generation feature to enable rendering highly accurate terrains based on any celestial body’s digital elevation model (DEM) in GeoTIFF format. These improvements notably elevate the visualization tool's functionality, accuracy, and user interaction while providing a robust foundation for future development.

Visualization↗

NASA NTRS2010

Evaluating the Performance of Unmanned Ground Vehicle Water Detection

Water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation over cross-country terrain. During the Robotics Collaborative Technology Alliances (RCTA) program, the Jet Propulsion Laboratory (JPL) developed a set of water detection algorithms that are used to detect, localize, and avoid water bodies large enough to be a hazard to a UGV. The JPL water detection software performs the detection and localization stages using a forward-looking stereo pair of color cameras. The 3D coordinates of water body surface points are then output to a UGV's autonomous mobility system, which is responsible for planning and executing safe paths. There are three primary methods for evaluating the performance of the water detection software. Evaluations can be performed in image space on the intermediate detection product, in map space on the final localized product, or during autonomous navigation to characterize the avoidance of a variety of water bodies. This paper describes a methodology for performing the first two types of water detection performance evaluations.

stereo vision↗

NASA NTRS1989

Structural stereo matching of Laplacian-of-Gaussian contour segments for 3D perception

The stereo correspondence problem is solved using Laplacian-of-Gaussian zero-crossing contours as a source of primitives for structural stereopsis, as opposed to traditional point-based algorithms. Up to 74 percent matching of candidate zero crossing points are being achieved on 240 x 246 images at small scales and large ranges of disparity, without coarse-to-fine tracking and without precise knowledge of the epipolar geometry. This approach should prove particularly useful in recovering the epipolar geometry automatically for stereo pairs for which it is unavailable a priori. Such situations occur in the extraction of terrain models from stereo aerial photographs.

Boyer, K. L.↗

NASA NTRS2011

3D Vegetation Mapping Using UAVSAR, LVIS, and LIDAR Data Acquisition Methods

The overarching objective of this ongoing project is to assess the role of vegetation within climate change. Forests capture carbon, a green house gas, from the atmosphere. Thus, any change, whether, natural (e.g. growth, fire, death) or due to anthropogenic activity (e.g. logging, burning, urbanization) may have a significant impact on the Earth's carbon cycle. Through the use of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and NASA's Laser Vegetation Imaging Sensor (LVIS), which are airborne Light Detection and Ranging (LIDAR) remote sensing technologies, we gather data to estimate the amount of carbon contained in forests and how the content changes over time. UAVSAR and LVIS sensors were sent all over the world with the objective of mapping out terrain to gather tree canopy height and biomass data; This data is in turn used to correlate vegetation with the global carbon cycle around the world.

Uninhabited Aerial Vehicle Synthetic Aperture Rada↗

NASA NTRS2022

On-board Absolute Localization Based on Orbital Imagery for a Future Mars Science Helicopter

Future Mars Rotorcraft require advanced navigationcapabilities to enable all terrain access over long distance flightsthat are executed fully autonomously. A critical component toenable precision navigation during long traverses is the abilityto perform on-board absolute localization to eliminate drift inposition estimates of the on-board odometry algorithm. Inthis paper, we present an approach for on-board map-basedlocalization to provide global reference position based on orbitalor aerial image maps. Our approach builds on a vision-basedlocalization method to localize against a map derived fromHiRISE image products – an ortho-projected image (orthoimage) and a corresponding digital elevation map. The mapis pre-computed using a feature-based approach. Features arestored with their 3D world coordinates, and a descriptor to codethe local image intensity information in the vicinity of the featurelocation. An on-board matching algorithm uses this informationto match visual features in a query image acquired during flight,guided by a pose prior from the on-board range-visual-inertialstate estimator (Range-VIO). Valid matches are then used bya perspective-n-point (PnP) algorithm to estimate the absolutepose of the vehicle in a global frame. We demonstrate andevaluate our approach on simulated data, and data from UASflights.

Balaram, J. Bob↗

NASA NTRS2019

Marsbee - Swarm of Flapping Wing Flyers for Enhanced Mars Exploration: NASA Innovative Advanced Concepts (NIAC) - Phase I: Final Report

Mars exploration has received significant interest from academia, industry, government, and the general public. Despite continued interest, flying on Mars remains challenging, mainly due to the ultra-thin Martian atmospheric density. Although the gravitational acceleration on Mars is 38 percent of Earth's 9.8 meters per second squared, the Martian atmospheric density is only 1.3 percent of the air density on Earth. The aerodynamic forces are proportional to the ambient fluid density. Therefore, flying near the surface of Mars has been considered nearly impossible. The proposed mission architecture (Fig. 1) consists of a Mars rover (already existing) that serves as a mobile base for Marsbees - a deployable swarm of small bio-inspired flapping wing vehicles. In one ConOps scenario, each Marsbee would carry an integrated stereographic video camera and the swarm could construct a 3D topographic map of the local surface for rover path planning. These flying scouts would provide a "third-dimension" to the rover capabilities. In other scenarios, each part of the swarm of Marsbees could carry pressure and temperature sensors for atmospheric sampling, or small spectral analyzers for identification of mineral outcroppings. In each scenario, the rover acts as a recharging and deployment/return station and data and communication hub. Human exploration of Mars is one of the major objectives of NASA and commercial entities such as SpaceX and Boeing. The identified innovations unique to the bio-inspired flapping Marsbee provide viable multi-mode flying mobility for Martian atmospheric and terrain exploration. A swarm of Marsbees provides an enhanced reconfigurable Mars exploration system that is resilient to individual component failures. These Marsbees can carry sensors and wireless communication devices in combination with a Mars rover and helicopters. These enhanced sensing and information gathering abilities can contribute to the following NASA Mars mission objectives: i) "Determine the habitability of an environment", ii) "Obtain surface weather measurements to validate global atmospheric models", and iii) "Prepare for human exploration on Mars." Various commercial entities, e.g. SpaceX and Boeing, are investing in technologies to transport humans to Mars.

Kang, Chang-kwon↗

NASA NTRS2020

Analysis of Sample Acquisition Dynamics Using Discrete Element Method

The analysis presented in this paper is conducted in the framework of the Ocean Worlds Autonomy Testbed for Exploration Research and Simulation (OceanWATERS) project, currently under development at NASA Ames Research Center. OceanWATERS aims at designing a simulation environment which allows for testing autonomy of scientific lander missions to the icy moons of our solar system. Mainly focused on reproducing the end effector interaction with the inherent terrain, this paper introduces a novel discrete element method (DEM)-based approach to determine forces and torques acting on the lander’s scoop during the sample acquisition process. An accurate force feedback from the terrain on the scoop is required by fault-detection and autonomous decision-making algorithms to identify when the requested torque on the robotic arm’s joints exceeds the maximum available torque. Knowledge of the terrain force feedback significantly helps evaluating the arm’s links structural properties and properly selecting actuators for the joints. Models available in literature constitute a partial representation of the dynamics of the interaction. As an example, Balovnev derived an analytical expression of the vertical and horizontal force acting on a bucket while collecting a sample as a function of its geometry and velocity, soil parameters and reached depth. Although the model represents an adequate approximation of the two force components, it ignores the direction orthogonal to the scoop motion and neglects the torque. This work relies on DEM analysis to compensate for analytical models’ deficiencies and inaccuracies, i. e. provide force and torque 3D vectors, defined in the moving reference (body) frame attached to the scoop, at each instant of the sample collection process. Results from the first presented analysis relate to the specific OceanWATERS sampling strategy, which consists of collecting the sample through five consecutive passes with increasing depth, each pass following the same circularlinear- circular trajectory. Data is collected given a specific scoop design interacting with two types of bulk materials, which may characterize the surface of icy planetary bodies: snow and ice. Although specifically concerned with the OceanWATERS design, this first analysis provides the expected force trends for similar sampling strategies and allows to deduce phenomenological information about the general scooping process. In order to further instruct the community on the use of DEM tools as a solution to the sampling collection problem, two more analyses have been carried out, mainly focused on reducing the DEM computation time, which increases with a decrease in particle size. After running a set of identical simulations, where the only changing parameter is the size of the spherical particle, it is observed that the resulting force trajectories, starting from a given particle size, converge to the true trend. It is deducible that a further decrease in size yields negligible improvements in the accuracy, while it sensibly increases computation time. A final analysis aims at discussing limitations of approximating bulk material particles having a complex shape, e. g. ice fragments, with spheres, by comparing force trends resulting in the two cases for the same simulation scenario.

Catanoso, Damiana↗

NASA NTRS1991

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

Schenker, Paul S.↗

NASA NTRS2020

High-capacity ATHLETE Offloader Mobility Constructor Concept for Human Surface Exploration

Using cross-cabled, winch-tendon four-bar frames, a new Artemis-class ATHLETE system is a multi-limbed robotic mobility platform that is designed for surface traverse, precision placement, and offloading of heavy habitats and other large human exploration payloads from high-decked landers. Building upon lessons learned from the All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE) robotic mobility system developed for Constellation Lunar Surface Systems and Evolvable Mars Campaign, a high-capacity articulated crane / lift vehicle concept has been devised that would be equipped with multi-limb six-degree-of-freedom dexterity for a variety of tasks supporting planetary surface human exploration missions and outposts. The Artemis-class ATHLETE vehicle would use any combination of three to six wheel-onlimb combinations to provide a wide “outrigger” stance to transfer loads from a high center-of-gravity on sloped terrain to low stable carry configurations for long-distance traverses, and be capable of precision docking of payloads to previously positioned elements. The new vehicle concept improves upon previous Constellation-class ATHLETE versions by allowing modular hot-swapping of individual limbs to improve maintenance and flexibility. The extreme-capacity independent limbs can individually function as single cranes, and can be delivered separately via multiple lander manifests for later congregation into self-driving “Tri-ATHLETE” vehicles after delivery to the surface. This paper provides mission architecture targets and vehicle masses for stepped payload capacity values in Earth, Mars, and Lunar gravity environments, and discusses a variety of swappable tools, including wheeled mobility attachments, grippers, excavation tools, repair fixtures, ISRU extraction, winches, block & tackle rigging combinations, 3D printheads, and construction aids.

Wilcox, Brian↗

NASA NTRS2011

Gripping Mechanisms for Microgravity and Extreme Terrain and Vertical Climbing Micro Ground Vehicle

Asteroids and comets may provide insight into the origins of our solar system and the precursors to life on our planet. Near Earth objects offer an accessible target of opportunity, but are small and lack the gravity necessary for conventional wheeled travel. Therefore, it is necessary to develop alternative methods for maneuvering in these environments. This project researched and developed a method for gripping rock surfaces. Work has been completed on the design and prototyping of several possible hooked gripping mechanisms. Future work includes quantitative testing, downselection to a final design, and attachment to the robotic platform, Lemur IIb. A second project focuses on the development of a 100g, crash-proof robot capable of climbing vertical surfaces using a novel silicone adhesive. Capable of carrying video/audio payloads the robot may serve as a surveillance tool for the Department of Defense or as a method of pre-flight spacecraft inspections. A specialized track was developed to provide the specific loading conditions necessary for proper engagement of the adhesive. Both of these projects rely heavily on the shape deposition manufacturing process, being researched at JPL, and 3D printing.

robotic locomotion↗

NASA NTRS2007

Mapped Landmark Algorithm for Precision Landing

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

Johnson, Andrew↗

NASA NTRS2010

JMISR INteractive eXplorer

MISR (Multi-angle Imaging SpectroRadiometer) INteractive eXplorer (MINX) is an interactive visualization program that allows a user to digitize smoke, dust, or volcanic plumes in MISR multiangle images, and automatically retrieve height and wind profiles associated with those plumes. This innovation can perform 9-camera animations of MISR level-1 radiance images to study the 3D relationships of clouds and plumes. MINX also enables archiving MISR aerosol properties and Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power along with the heights and winds. It can correct geometric misregistration between cameras by correlating off-nadir camera scenes with corresponding nadir scenes and then warping the images to minimize the misregistration offsets. Plots of BRF (bidirectional reflectance factor) vs. camera angle for points clicked in an image can be displayed. Users get rapid access to map views of MISR path and orbit locations and overflight dates, and past or future orbits can be identified that pass over a specified location at a specified time. Single-camera, level-1 radiance data at 1,100- or 275- meter resolution can be quickly displayed in color using a browse option. This software determines the heights and motion vectors of features above the terrain with greater precision and coverage than previous methods, based on an algorithm that takes wind direction into consideration. Human interpreters can precisely identify plumes and their extent, and wind direction. Overposting of MODIS thermal anomaly data aids in the identification of smoke plumes. The software has been used to preserve graphical and textural versions of the digitized data in a Web-based database.

Nelson, David L.↗

NASA NTRS2011

High-Performance 3D Articulated Robot Display

In the domain of telerobotic operations, the primary challenge facing the operator is to understand the state of the robotic platform. One key aspect of understanding the state is to visualize the physical location and configuration of the platform. As there is a wide variety of mobile robots, the requirements for visualizing their configurations vary diversely across different platforms. There can also be diversity in the mechanical mobility, such as wheeled, tracked, or legged mobility over surfaces. Adaptable 3D articulated robot visualization software can accommodate a wide variety of robotic platforms and environments. The visualization has been used for surface, aerial, space, and water robotic vehicle visualization during field testing. It has been used to enable operations of wheeled and legged surface vehicles, and can be readily adapted to facilitate other mechanical mobility solutions. The 3D visualization can render an articulated 3D model of a robotic platform for any environment. Given the model, the software receives real-time telemetry from the avionics system onboard the vehicle and animates the robot visualization to reflect the telemetered physical state. This is used to track the position and attitude in real time to monitor the progress of the vehicle as it traverses its environment. It is also used to monitor the state of any or all articulated elements of the vehicle, such as arms, legs, or control surfaces. The visualization can also render other sorts of telemetered states visually, such as stress or strains that are measured by the avionics. Such data can be used to color or annotate the virtual vehicle to indicate nominal or off-nominal states during operation. The visualization is also able to render the simulated environment where the vehicle is operating. For surface and aerial vehicles, it can render the terrain under the vehicle as the avionics sends it location information (GPS, odometry, or star tracking), and locate the vehicle over or on the terrain correctly. For long traverses over terrain, the visualization can stream in terrain piecewise in order to maintain the current area of interest for the operator without incurring unreasonable resource constraints on the computing platform. The visualization software is designed to run on laptops that can operate in field-testing environments without Internet access, which is a frequently encountered situation when testing in remote locations that simulate planetary environments such as Mars and other planetary bodies.

Powell, Mark W.↗

NASA NTRS2013

Building a 2.5D Digital Elevation Model from 2D Imagery

When projecting imagery into a georeferenced coordinate frame, one needs to have some model of the geographical region that is being projected to. This model can sometimes be a simple geometrical curve, such as an ellipse or even a plane. However, to obtain accurate projections, one needs to have a more sophisticated model that encodes the undulations in the terrain including things like mountains, valleys, and even manmade structures. The product that is often used for this purpose is a Digital Elevation Model (DEM). The technology presented here generates a high-quality DEM from a collection of 2D images taken from multiple viewpoints, plus pose data for each of the images and a camera model for the sensor. The technology assumes that the images are all of the same region of the environment. The pose data for each image is used as an initial estimate of the geometric relationship between the images, but the pose data is often noisy and not of sufficient quality to build a high-quality DEM. Therefore, the source imagery is passed through a feature-tracking algorithm and multi-plane-homography algorithm, which refine the geometric transforms between images. The images and their refined poses are then passed to a stereo algorithm, which generates dense 3D data for each image in the sequence. The 3D data from each image is then placed into a consistent coordinate frame and passed to a routine that divides the coordinate frame into a number of cells. The 3D points that fall into each cell are collected, and basic statistics are applied to determine the elevation of that cell. The result of this step is a DEM that is in an arbitrary coordinate frame. This DEM is then filtered and smoothed in order to remove small artifacts. The final step in the algorithm is to take the initial DEM and rotate and translate it to be in the world coordinate frame [such as UTM (Universal Transverse Mercator), MGRS (Military Grid Reference System), or geodetic] such that it can be saved in a standard DEM format and used for projection.

Padgett, Curtis W.↗