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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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At least 109 records · Page 6
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NASA NTRS1993

A parallel implementation of a multisensor feature-based range-estimation method

There are many proposed vision based methods to perform obstacle detection and avoidance for autonomous or semi-autonomous vehicles. All methods, however, will require very high processing rates to achieve real time performance. A system capable of supporting autonomous helicopter navigation will need to extract obstacle information from imagery at rates varying from ten frames per second to thirty or more frames per second depending on the vehicle speed. Such a system will need to sustain billions of operations per second. To reach such high processing rates using current technology, a parallel implementation of the obstacle detection/ranging method is required. This paper describes an efficient and flexible parallel implementation of a multisensor feature-based range-estimation algorithm, targeted for helicopter flight, realized on both a distributed-memory and shared-memory parallel computer.

Suorsa, Raymond E.↗
NASA NTRS1992

Automatic rule generation for high-level vision

A new fuzzy set based technique that was developed for decision making is discussed. It is a method to generate fuzzy decision rules automatically for image analysis. This paper proposes a method to generate rule-based approaches to solve problems such as autonomous navigation and image understanding automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.

Rhee, Frank Chung-Hoon↗
NASA NTRS2019

Planetary Rover Simulation for Lunar Exploration Missions

When planning planetary rover missions it is useful to develop intuition and skills driving in, quite literally, alien environments before incurring the cost of reaching said locales. Simulators make it possible to operate in environments that have the physical characteristics of target locations without the expense and overhead of extensive physical tests. To that end, NASA Ames and Open Robotics collaborated on a Lunar rover driving simulator based on the open source Gazebo simulation platform and leveraging ROS (Robotic Operating System) components. The simulator was integrated with research and mission software for rover driving, system monitoring, and science instrument simulation to constitute an end-to-end Lunar mission simulation capability. Although we expect our simulator to be applicable to arbitrary Lunar regions, we designed to a reference mission of prospecting in polar regions. The harsh lighting and low illumination angles at the Lunar poles combine with the unique reflectance properties of Lunar regolith to present a challenging visual environment for both human and computer perception. Our simulator placed an emphasis on high fidelity visual simulation in order to produce synthetic imagery suitable for evaluating human rover drivers with navigation tasks, as well as providing test data for computer vision software development.In this paper, we describe the software used to construct the simulated Lunar environment and the components of the driving simulation. Our synthetic terrain generation software artificially increases the resolution of Lunar digital elevation maps by fractal synthesis and inserts craters and rocks based on Lunar size-frequency distribution models. We describe the necessary enhancements to import large scale, high resolution terrains into Gazebo, as well as our approach to modeling the visual environment of the Lunar surface. An overview of the mission software system is provided, along with how ROS was used to emulate flight software components that had not been developed yet. Finally, we discuss the effect of using the high-fidelity synthetic Lunar images for visual odometry. We also characterize the wheel slip model, and find some inconsistencies in the produced wheel slip behaviour.

Allan, Mark↗
NASA NTRS2022

Vision-Based Precision Approach and Landing for Advanced Air Mobility

Advanced Air Mobility (AAM) aircraft require perception systems for precision approach and landing systems (PALS) in urban, suburban, rural, and regional environments. The current state-of-the-art methods approved for automated approach and landing will be difficult to utilize in support of AAM operational concepts. However, there are technology and systems from other applications and lower-TRL research that use vision, IR, radar, and GPS methods to provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL to demonstrate a closed-loop baseline controller while adhering to the Federal Aviation Administration requirements and regulations. The coplanar algorithm determines pose estimation, which feeds into an Extended Kalman filter. Combining IMU with vision creates a sensor fusion navigation solution for GPS-denied environments. The state estimate leads to glideslope and localizer error computations, which will be pertinent for designing and deriving guidance laws and control laws for AAM PALS. The IMU and vision navigation solution provides promising simulation results for AAM PALS, and higher fidelity simulations will include computer graphics rendering and feature correspondence.

Evan Kawamura↗
NASA NTRS1992

Achieving safe autonomous landings on Mars using vision-based approaches

Autonomous landing capabilities will be critical to the success of planetary exploration missions, and in particular to the exploration of Mars. Past studies have indicated that the probability of failure associated with open-loop landings is unacceptably high. Two approaches to achieving autonomous landings with higher probabilities of success are currently under analysis. If a landing site has been certified as hazard free, then navigational aids can be used to facilitate a precision landing. When only limited surface knowledge is available and landing areas cannot be certified as hazard free, then a hazard detection and avoidance approach can be used, in which the vehicle selects hazard free landing sites in real-time during its descent. Issues pertinent to both approaches, including sensors and algorithms, are presented. Preliminary results indicate that one promising approach to achieving high accuracy precision landing is to correlate optical images of the terrain acquired during the terminal descent phase with a reference image. For hazard detection scenarios, a sensor suite comprised of a passive intensity sensor and a laser ranging sensor appears promising as a means of achieving robust landings.

Pien, Homer↗
NASA NTRS2021

Assessment of M2020 Terrain Relative Landing Accuracy: Flight Performance vs Predicts

Terrain Relative Navigation (TRN) was a critical enabling Entry, Descent, and Landing (EDL) technology that enabled Mars 2020 mission Perseverance rover to land at Jezero crater. TRN pro-vides real-time, autonomous, map-relative position determination and generates a landing target based on a priori knowledge of hazards. The required performance for TRN was to land within 60m of the selected target. The required 60m was sub-allocated to various error sources in three major categories: targeting error, knowledge error, and control error. The targeting error is the error in selecting an appropriate landing target and the knowledge of the target on the surface. It includes the Lander Vision System (LVS) position localization with respect the ground, the synchronization between the Lander Vision System measurement and the main Navigation filter, and errors associated with the LVS Reference Map and Safe Target Selec-tion (STS). The knowledge error is the contribution of knowledge growth from the synchronization with LVS to touchdown. The control error encompasses how accurately the system could stay on the desired reference trajectory. The TRN error budget uses a combination of analysis, simulation, and hardware test-ing results to bound the various error contributions obtained during the verification and validation process. This paper first presents a description the TRN system, focusing on the architecture of LVS and STS. The paper then gives detailed overview of the TRN error budget, with a description of the major error contribu-tions in each of the three categories. Next, the paper gives the results for three versions of the error budget, pre-launch, in-flight pre-landing, and post-landing. The paper compares the pre-flight analysis, the pre-landing analysis using in-flight data during cruise, to the post-landing analysis of the TRN performance. Pre-landing analysis best estimate of the landing performance was 33m, compared to the 60m require-ment. Post-landing analysis estimated a landing accuracy of 8.53m or better, much better than the 33m pre-landing estimate. The actual post-landing imagery calculated the distance of the rover to the targeted location to be 5m. The post-landing analysis closely bounds the image-based assessment of landing accu-racy, indicating the success of the error budget architecture in bounding the landing accuracy, as well as the fidelity of the simulations used to model and predict performance.

Chen, Allen↗
NASA NTRS2010

Effects of a Velocity-Vector Based Command Augmentation System and Synthetic Vision System Terrain Portrayal and Guidance Symbology Concepts on Single-Pilot Performance

This study investigated the effects of synthetic vision system (SVS) concepts and advanced flight controls on the performance of pilots flying a light, single-engine general aviation airplane. We evaluated the effects and interactions of two levels of terrain portrayal, guidance symbology, and flight control response type on pilot performance during the conduct of a relatively complex instrument approach procedure. The terrain and guidance presentations were evaluated as elements of an integrated primary flight display system. The approach procedure used in the study included a steeply descending, curved segment as might be encountered in emerging, required navigation performance (RNP) based procedures. Pilot performance measures consisted of flight technical performance, perceived workload, perceived situational awareness and subjective preference. The results revealed that an elevation based generic terrain portrayal significantly improved perceived situation awareness without adversely affecting flight technical performance or workload. Other factors (pilot instrument rating, control response type, and guidance symbology) were not found to significantly affect the performance measures.

Liu, Dahai↗
NASA NTRS2005

Human Exploration and Avionic Technology Challenges

For this workshop, I will identify critical avionic gaps, enabling technologies, high-pay off investment opportunities, promising capabilities, and space applications for human lunar and Mars exploration. Key technology disciplines encompass fault tolerance, miniaturized instrumentation sensors, MEMS-based guidance, navigation, and controls, surface communication networks, and rendezvous and docking. Furthermore, I will share bottom-up strategic planning relevant to manned mission -driven needs. Blending research expertise, facilities, and personnel with internal NASA is vital to stimulating collaborative technology solutions that achieve NASA grand vision. Retaining JSC expertise in unique and critical areas is paramount to our long-term success. Civil servants will maintain key roles in setting technology agenda, ensuring quality results, and integrating technologies into avionic systems and manned missions. Finally, I will present to NASA, academia, and the aerospace community some on -going and future advanced avionic technology programs and activities that are relevant to our mission goals and objectives.

Benjamin, Andrew L.↗
NASA NTRS1999

Insect-Based Vision for Autonomous Vehicles: A Feasibility Study

The aims of the project were to use a high-speed digital video camera to pursue two questions: i) To explore the influence of temporal imaging constraints on the performance of vision systems for autonomous mobile robots; To study the fine structure of insect flight trajectories with in order to better understand the characteristics of flight control, orientation and navigation.

Srinivasan, Mandyam V.↗
NASA NTRS1999

Insect-Based Vision for Autonomous Vehicles: A Feasibility Study

The aims of the project were to use a high-speed digital video camera to pursue two questions: (1) To explore the influence of temporal imaging constraints on the performance of vision systems for autonomous mobile robots; (2) To study the fine structure of insect flight trajectories in order to better understand the characteristics of flight control, orientation and navigation.

Srinivasan, Mandyam V.↗
NASA NTRS2005

Target Tracking, Approach, and Camera Handoff for Automated Instrument Placement

This paper describes the target designation, tracking, approach, and camera handoff technologies required to achieve accurate, single-command autonomous instrument placement for a planetary rover. It focuses on robust tracking integrated with obstacle avoidance during the approach phase, and image-based camera handoff to allow vision-based instrument placement. It also provides initial results from a complete system combining these technologies with rover base placement to maximize arm manipulability and image-based instrument placement.

target tracking↗
NASA NTRS2018

Cobalt: Terrestrial Flight Test of Landing Navigation Using Lander Vision System with Navigation Doppler Lidar

COBALT (CoOperative Blending of Autonomous Landing Technologies) is a NASA technology development and test program to advance precision landing capabilities for future soft landers. The COBALT payload demonstrated terrain relative navigation utilizing the Lander Vision System and Navigation Doppler Lidar sensors on the Masten Space Systems Xodiac rocket. In spring 2017, the program culminated in two open-loop free flights to 500 m altitude with downrange diverts of 300 m. The COBALT system performed well, navigating within meters of the Xodiac vehicle’s GPS-based solution. This paper outlines details of the navigation filter and its performance during the test campaign.

Carson, John M. III↗
NASA NTRS2004

Two-Armed, Mobile, Sensate Research Robot

The Anthropomorphic Robotic Testbed (ART) is an experimental prototype of a partly anthropomorphic, humanoid-size, mobile robot. The basic ART design concept provides for a combination of two-armed coordination, tactility, stereoscopic vision, mobility with navigation and avoidance of obstacles, and natural-language communication, so that the ART could emulate humans in many activities. The ART could be developed into a variety of highly capable robotic assistants for general or specific applications. There is especially great potential for the development of ART-based robots as substitutes for live-in health-care aides for home-bound persons who are aged, infirm, or physically handicapped; these robots could greatly reduce the cost of home health care and extend the term of independent living. The ART is a fully autonomous and untethered system. It includes a mobile base on which is mounted an extensible torso topped by a head, shoulders, and two arms. All subsystems of the ART are powered by a rechargeable, removable battery pack. The mobile base is a differentially- driven, nonholonomic vehicle capable of a speed >1 m/s and can handle a payload >100 kg. The base can be controlled manually, in forward/backward and/or simultaneous rotational motion, by use of a joystick. Alternatively, the motion of the base can be controlled autonomously by an onboard navigational computer. By retraction or extension of the torso, the head height of the ART can be adjusted from 5 ft (1.5 m) to 6 1/2 ft (2 m), so that the arms can reach either the floor or high shelves, or some ceilings. The arms are symmetrical. Each arm (including the wrist) has a total of six rotary axes like those of the human shoulder, elbow, and wrist joints. The arms are actuated by electric motors in combination with brakes and gas-spring assists on the shoulder and elbow joints. The arms are operated under closed-loop digital control. A receptacle for an end effector is mounted on the tip of the wrist and contains a force-and-torque sensor that provides feedback for force (compliance) control of the arm. The end effector could be a tool or a robot hand, depending on the application.

Engelberger, J. F.↗
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 NTRS2009

A Kalman Approach to Lunar Surface Navigation using Radiometric and Inertial Measurements

Future lunar missions supporting the NASA Vision for Space Exploration will rely on a surface navigation system to determine astronaut position, guide exploration, and return safely to the lunar habitat. In this report, we investigate one potential architecture for surface navigation, using an extended Kalman filter to integrate radiometric and inertial measurements. We present a possible infrastructure to support this technique, and we examine an approach to simulating navigational accuracy based on several different system configurations. The results show that position error can be reduced to 1 m after 5 min of processing, given two satellites, one surface communication terminal, and knowledge of the starting position to within 100 m.

Chelmins, David T.↗
NASA NTRS2010

Personal Aircraft Point to the Future of Transportation

NASA's Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs, as well as a number of Agency innovations, have helped Duluth, Minnesota-based Cirrus Design Corporation become one of the world's leading manufacturers of general aviation aircraft. SBIRs with Langley Research Center provided the company with cost-effective composite airframe manufacturing methods, while crashworthiness testing at the Center increased the safety of its airplanes. Other NASA-derived technologies on Cirrus SR20 and SR22 aircraft include synthetic vision systems that help pilots navigate and full-plane parachutes that have saved the lives of more than 30 Cirrus pilots and passengers to date. Today, the SR22 is the world's top-selling Federal Aviation Administration (FAA)-certified single-engine airplane.

Source record↗
NASA NTRS1991

Navigation of military and space unmanned ground vehicles in unstructured terrains

Development of unmanned vehicles for local navigation in terrains unstructured by humans is reviewed. Modes of navigation include teleoperation or remote control, computer assisted remote driving (CARD), and semiautonomous navigation (SAN). A first implementation of a CARD system was successfully tested using the Robotic Technology Test Vehicle developed by Jet Propulsion Laboratory. Stereo pictures were transmitted to a remotely located human operator, who performed the sensing, perception, and planning functions of navigation. A computer provided range and angle measurements and the path plan was transmitted to the vehicle which autonomously executed the path. This implementation is to be enhanced by providing passive stereo vision and a reflex control system for autonomously stopping the vehicle if blocked by an obstacle. SAN achievements include implementation of a navigation testbed on a six wheel, three-body articulated rover vehicle, development of SAN algorithms and code, integration of SAN software onto the vehicle, and a successful feasibility demonstration that represents a step forward towards the technology required for long-range exploration of the lunar or Martian surface. The vehicle includes a passive stereo vision system with real-time area-based stereo image correlation, a terrain matcher, a path planner, and a path execution planner.

Lescoe, Paul↗
NASA NTRS2021

The Mars 2020 Perseverance Navigation Filter

The Mars 2020 (M2020) Entry Descent and Landing (EDL) system delivered a rover named “Perseverance” at Jezero crater (Mars) on February 18th, 2021. M2020 EDL used a Guidance Navigation and Control (GN&C) system to achieve its landing target objectives. The navigation filter (NavFilter) integrated Descent Inertial Measurement Unit (DIMU) measurements to estimate position and attitude. The NavFilter also used the Terminal Descent Sensor (TDS) to es-timate surface-relative position and velocity corrections. The NavFilter provided all of the dynamic state information to the entry controller, entry guidance, Lander Vision System (LVS) and powered descent guidance and control algo-rithms. The NavFilter for Perseverance is based on Curiosity’s NavFilter with a couple of modifications.

Casoliva, Jordi↗