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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Methods and Comparisons Between Computer Vision and Radar Based Vehicle Location

Measuring vehicle locations relative to a driver's vehicle is a critical component in the analysis of driving data from both postanalysis (such as in naturalistic driving studies) or in autonomous vehicle navigation. In this work we describe a method to estimate vehicle positions from a forward-looking video camera using intrinsic camera calibration, estimates of extrinsic parameters, and a convolutional neural network trained to detect and locate vehicles in video data. We compare the measurements we achieve with this method with ground truth and with radar data available from a naturalistic driving study. We identify regions where video is preferred, where radar is preferred, and explore trade-offs between the two methods in regions where the preference is more ambiguous. We describe applications of these measurements for transportation analysis.

Aykac, Deniz↗
NASA NTRS1981

Relative performance of algorithms for autonomous satellite orbit determination

Limited word size in contemporary microprocessors causes numerical problems in autonomous satellite navigation applications. Numerical error introduced in navigation computations performed on small wordlength machines can cause divergence of sequential estimation algorithms. To insure filter reliability, square root algorithms have been adopted in many applications. The optimal navigation algorithm requires a careful match of the estimation algorithm, dynamic model, and numerical integrator. In this investigation, the relationship of several square root filters and numerical integration methods is evaluated to determine their relative performance for satellite navigation applications. The numerical simulations are conducted using the Phase I GPS constellation to determine the orbit of a LANDSAT-D type satellite. The primary comparison is based on computation time and relative estimation accuracy.

Tapley, B. D.↗
NASA NTRS1984

An approach to autonomous, onboard orbit determination

An orbit determination subsystem that will operate as an integral part of an autonomous, onboard navigation system is presented and analyzed. The navigation system is required to interface solely with the downlink telemetry stream and uplink command stream of an existing class of geostationary satellites. In particular, the orbit will be determined from a set of onboard sensors, which previously were used only for attitude determination. The design of the orbit determination subsystem is described in detail. The rationale behind the choice of each component of the design is given. Finally, the performance of the orbit determination subsystem, under a variety of assumptions, is determined by a combination of numerical simulation and analytical methods.

Mease, K. D.↗
NASA NTRS1989

Passive navigation using image irradiance tracking

Rotorcraft operating at low altitudes require navigational schemes for locating the terrain and obstacles. Due to the covert nature of missions to be accomplished, a passive navigation scheme is desirable. This paper describes the development of a passive navigation scheme combining image sequences from a vehicle mounted camera with vehicle motion variables. Geometric properties of perspective projection together with an image irradiance tracking scheme at each pixel are used to determine the range to various objects within the field-of-view. Derivation of the numerical algorithm and simulation results are given. Other applications of the proposed approach include navigation for autonomous planetary rovers and telerobots.

Menon, P. K. A.↗
NASA NTRS1990

Passive navigation using image irradiance tracking

Rotorcraft operating at low altitudes require navigational schemes for detecting terrain and obstacles. Due to the nature of the missions to be accomplished and available power onboard, a passive navigation scheme is desirable in this situation. The development of a passive navigation scheme using optical image sequences and vehicle motion variables from an onboard inertial navigation scheme is described. This approach combines the geometric properties of perspective projection and a feedback irradiance tracking scheme at each pixel in the image to determine the range to various objects within the field-of-view. Derivation of the numerical algorithm and simulation results are given. Due to the feedback nature of the implementation, the computational scheme is robust. Other applications of the proposed approach include navigation for autonomous planetary rovers and telerobots.

Menon, P. K. A.↗
NASA NTRS1992

Microrover Operates With Minimal Computation

Small, light, highly mobile robotic vehicles called "microrovers" use sensors and artificial intelligence to perform complicated tasks autonomously. Vehicle navigates, avoids obstacles, and picks up objects using reactive control scheme selected from among few preprogrammed behaviors to respond to environment while executing assigned task. Under development for exploration and mining of other planets. Also useful in firefighting, cleaning up chemical spills, and delivering materials in factories. Reactive control scheme and principle of behavior-description language useful in reducing computational loads in prosthetic limbs and automotive collision-avoidance systems.

Miller, David P.↗
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 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 NTRS2003

Bio-inspired Computing for Robots

Living creatures may provide algorithms to enable active sensing/control systems in robots. Active sensing could enable planetary rovers to feel their way in unknown environments. The surface of Jupiter's moon Europa consists of fractured ice over a liquid sea that may contain microbes similar to those on Earth. To explore such extreme environments, NASA needs robots that autonomously survive, navigate, and gather scientific data. They will be too far away for guidance from Earth. They must sense their environment and control their own movements to avoid obstacles or investigate a science opportunity. To meet this challenge, CICT's Information Technology Strategic Research (ITSR) Project is funding neurobiologists at NASA's Jet Propulsion Laboratory (JPL) and selected universities to search for biologically inspired algorithms that enable robust active sensing and control for exploratory robots. Sources for these algorithms are living creatures, including rats and electric fish.

Laufenberg, Larry↗
NASA NTRS2001

Deep Impact: 19 gigajoules can make quite an impression

Deep Impact will impact the comet Tempel-1 on July 4, 2005. The impact event will be clearly visible from small telescopes on Earth, especially in the IR bands. When combined with observations taken from the Flyby spacecraft, this science data set will provide unique insight into the materials and structure within the comet, and the strength of the surface.

deep impact autonav autonomous navigation↗
NASA NTRS2000

Terrain Perception for DEMO III

The Demo III program has as its primary focus the development of autonomous mobility for a small rugged cross country vehicle. In this paper we report recent progress on both stereo-based obstacle detection and terrain cover color-based classification.

autonomous navigation color classification terrain↗
NASA NTRS2000

A Portable, Autonomous, Urban Reconnaissance Robot

Portable mobile robots, in the size class of 20 kg or less, could be extremely valuable as autonomous reconnaissance platforms in urban hostage situations and disaster relief.

mobile robot autonomous navigation↗
NASA NTRS2007

Crew/Robot Coordinated Planetary EVA Operations at a Lunar Base Analog Site

Under the direction of NASA's Exploration Technology Development Program, robots and space suited subjects from several NASA centers recently completed a very successful demonstration of coordinated activities indicative of base camp operations on the lunar surface. For these activities, NASA chose a site near Meteor Crater, Arizona close to where Apollo Astronauts previously trained. The main scenario demonstrated crew returning from a planetary EVA (extra-vehicular activity) to a temporary base camp and entering a pressurized rover compartment while robots performed tasks in preparation for the next EVA. Scenario tasks included: rover operations under direct human control and autonomous modes, crew ingress and egress activities, autonomous robotic payload removal and stowage operations under both local control and remote control from Houston, and autonomous robotic navigation and inspection. In addition to the main scenario, participants had an opportunity to explore additional robotic operations: hill climbing, maneuvering heaving loads, gathering geo-logical samples, drilling, and tether operations. In this analog environment, the suited subjects and robots experienced high levels of dust, rough terrain, and harsh lighting.

Diftler, M. A.↗
NASA NTRS2007

Slip Validation and Prediction for Mars Exploration Rovers

This paper presents a novel technique to validate and predict the rover slips on Martian surface for NASA's Mars Exploration Rovers. Different from the traditional approach, the proposed method uses the actual velocity profile of the wheels and the digital elevation map (DEM) from the stereo images of the terrain to formulate simplified equations of motion of the rovers. A weighted factor to the wheel-ground speed from the empirical data comprises the velocity equations of the simplified differential-algebraic system of the rover motion. Applying the discretization operator to these equations, the full kinematics state of the rover is then resolved by the configuration kinematics solution in the Robot Sequencing and Visualization Program (RSVP). This method produced accurate simulation of the rover movements compared with these of the earth testing vehicle. Using the telemetry from the onboard Visual Odometry, the simulated rover path also compares well with the actual track of the vehicle. Preliminary results indicated that the proposed computational method is very effective in planning the path of the rovers on the high-slope areas.

Mars Rovers↗