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Bulyshev, Alexander

Publications and source records attributed to Bulyshev, Alexander.

Advancing Lidar Sensors Technologies for Next Generation Landing Missions

Missions to solar systems bodies must meet increasingly ambitious objectives requiring highly reliable "precision landing", and "hazard avoidance" capabilities. Robotic missions to the Moon and Mars demand landing at pre-designated sites of high scientific value near hazardous terrain features, such as escarpments, craters, slopes, and rocks. Missions aimed at paving the path for colonization of the Moon and human landing on Mars need to execute onboard hazard detection and precision maneuvering to ensure safe landing near previously deployed assets. Asteroid missions require precision rendezvous, identification of the landing or sampling site location, and navigation to the highly dynamic object that may be tumbling at a fast rate. To meet these needs, NASA Langley Research Center (LaRC) has developed a set of advanced lidar sensors under the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project. These lidar sensors can provide precision measurement of vehicle relative proximity, velocity, and orientation, and high resolution elevation maps of the surface during the descent to the targeted body. Recent flights onboard Morpheus free-flyer vehicle have demonstrated the viability of ALHAT lidar sensors for future landing missions to solar system bodies.

Amzajerdian, Farzin↗

Three-Dimensional Super-Resolution: Theory, Modeling, and Field Tests Results

Many flash lidar applications continue to demand higher three-dimensional image resolution beyond the current state-of-the-art technology of the detector arrays and their associated readout circuits. Even with the available number of focal plane pixels, the required number of photons for illuminating all the pixels may impose impractical requirements on the laser pulse energy or the receiver aperture size. Therefore, image resolution enhancement by means of a super-resolution algorithm in near real time presents a very attractive solution for a wide range of flash lidar applications. This paper describes a superresolution technique and illustrates its performance and merits for generating three-dimensional image frames at a video rate.

Bulyshev, Alexander↗

A Super-Resolution Algorithm for Enhancement of FLASH LIDAR Data: Flight Test Results

This paper describes the results of a 3D super-resolution algorithm applied to the range data obtained from a recent Flash Lidar helicopter flight test. The flight test was conducted by the NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project over a simulated lunar terrain facility at NASA Kennedy Space Center. ALHAT is developing the technology for safe autonomous landing on the surface of celestial bodies: Moon, Mars, asteroids. One of the test objectives was to verify the ability of 3D super-resolution technique to generate high resolution digital elevation models (DEMs) and to determine time resolved relative positions and orientations of the vehicle. 3D super-resolution algorithm was developed earlier and tested in computational modeling, and laboratory experiments, and in a few dynamic experiments using a moving truck. Prior to the helicopter flight test campaign, a 100mX100m hazard field was constructed having most of the relevant extraterrestrial hazard: slopes, rocks, and craters with different sizes. Data were collected during the flight and then processed by the super-resolution code. The detailed DEM of the hazard field was constructed using independent measurement to be used for comparison. ALHAT navigation system data were used to verify abilities of super-resolution method to provide accurate relative navigation information. Namely, the 6 degree of freedom state vector of the instrument as a function of time was restored from super-resolution data. The results of comparisons show that the super-resolution method can construct high quality DEMs and allows for identifying hazards like rocks and craters within the accordance of ALHAT requirements.

Bulyshev, Alexander↗

Method for Enhancing a Three Dimensional Image from a Plurality of Frames of Flash LIDAR Data

A method for enhancing a three dimensional image from frames of flash LIDAR data includes generating a first distance R(sub i) from a first detector i to a first point on a surface S(sub i). After defining a map with a mesh theta having cells k, a first array S(k), a second array M(k), and a third array D(k) are initialized. The first array corresponds to the surface, the second array corresponds to the elevation map, and the third array D(k) receives an output for the DEM. The surface is projected onto the mesh theta, so that a second distance R(sub k) from a second point on the mesh theta to the detector can be found. From this, a height may be calculated, which permits the generation of a digital elevation map. Also, using sequential frames of flash LIDAR data, vehicle control is possible using an offset between successive frames.

Vanek, Michael D.↗

Helicopter Flight Test of 3-D Imaging Flash LIDAR Technology for Safe, Autonomous, and Precise Planetary Landing

Two flash lidars, integrated from a number of cutting-edge components from industry and NASA, are lab characterized and flight tested for determination of maximum operational range under the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project (in its fourth development and field test cycle) which is seeking to develop a guidance, navigation, and control (GN&C) and sensing system based on lidar technology capable of enabling safe, precise crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The flash lidars incorporate pioneering 3-D imaging cameras based on Indium-Gallium-Arsenide Avalanche Photo Diode (InGaAs APD) and novel micro-electronic technology for a 128 x 128 pixel array operating at 30 Hz, high pulse-energy 1.06 micrometer Nd:YAG lasers, and high performance transmitter and receiver fixed and zoom optics. The two flash lidars are characterized on the NASA-Langley Research Center (LaRC) Sensor Test Range, integrated with other portions of the ALHAT GN&C system from partner organizations into an instrument pod at NASA-JPL, integrated onto an Erickson Aircrane Helicopter at NASA-Dryden, and flight tested at the Edwards AFB Rogers dry lakebed over a field of human-made geometric hazards during the summer of 2010. Results show that the maximum operational range goal of 1 km is met and exceeded up to a value of 1.2 km. In addition, calibrated 3-D images of several hazards are acquired in real-time for later reconstruction into Digital Elevation Maps (DEM's).

Roback, Vincent↗

A Super-Resolution Algorithm for Enhancement of FLASH LIDAR data

A novel method for enhancement of the spatial resolution of 3-dimensional Flash Lidar images is being proposed for generation of elevation maps of terrain from a moving platform. NASA recognizes the Flash LIDAR technology as an important tool for enabling safe and precision landing in future unmanned and crewed lunar and planetary missions. The ability of the Flash LIDAR to generate 3-dimensional maps of the landing site area during the final stages of the descent phase for detection of hazardous terrain features such as craters, rocks, and steep slopes is under study in the frame of the Autonomous Landing and Hazard Avoidance (ALHAT) project. Since single frames of existing FLASH LIDAR systems are not sufficient to build a map of entire landing site with acceptable spatial resolution and precision, a super-resolution approach utilizing multiple frames has been developed to overcome the instrument s limitations. Performance of the super-resolution algorithm has been analyzed through a series of simulation runs obtained from a high fidelity Flash LIDAR model and a high resolution synthetic lunar elevation map. For each simulation run, a sequence of FLASH LIDAR frames are recorded and processed as the spacecraft descends toward the landing site. Simulations runs having different trajectory profiles and varying LIDAR look angles of the terrain are also analyzed. The results show that adequate levels of accuracy and precision are achieved for detecting hazardous terrain features and identifying safe areas of the landing site.

Bulyshev, Alexander↗

Super Resolution Image Enhancement for a Flash Lidar: Back Projection Method

In this paper a new image processing technique for flash LIDAR data is presented as a potential tool to enable safe and precise spacecraft landings in future robotic or crewed lunar and planetary missions. Flash LIDARs can generate, in real-time, range data that can be interpreted as a 3-dimensional (3-D) image and transformed into a corresponding digital elevation map (DEM). The NASA Autonomous Landing and Hazard Avoidance (ALHAT) project is capitalizing on this new technology by developing, testing and analyzing flash LIDARs to detect hazardous terrain features such as craters, rocks, and slopes during the descent phase of spacecraft landings. Using a flash LIDAR for this application looks very promising, however through theoretical and simulation analysis the ALHAT team has determined that a single frame, or mosaic, of flash LIDAR data may not be sufficient to build a landing site DEM with acceptable spatial resolution, precision, size, or for a mosaic, in time, to meet current system requirements. One way to overcome this potential limitation is by enhancing the flash LIDAR output images. We propose a new super-resolution algorithm applicable to flash LIDAR range data that will create a DEM with sufficient accuracy, precision and size to meet current ALHAT requirements. The performance of our super-resolution algorithm is analyzed by processing data generated during a series of simulation runs by a high fidelity model of a flash LIDAR imaging a high resolution synthetic lunar elevation map. The flash LIDAR model is attached to a simulated spacecraft by a gimbal that points the LIDAR to a target landing site. For each simulation run, a sequence of flash LIDAR frames is recorded and processed as the spacecraft descends toward the landing site. Each run has a different trajectory profile with varying LIDAR look angles of the terrain. We process the output LIDAR frames using our SR algorithm and the results show that the achieved level of accuracy and precision of the SR generated landing site DEM is more than adequate for detecting hazardous terrain features and identifying safe areas.

Bulyshev, Alexander↗

Utilization of 3-D Imaging Flash Lidar Technology for Autonomous Safe Landing on Planetary Bodies

NASA considers Flash Lidar a critical technology for enabling autonomous safe landing of future large robotic and crewed vehicles on the surface of the Moon and Mars. Flash Lidar can generate 3-Dimensional images of the terrain to identify hazardous features such as craters, rocks, and steep slopes during the final stages of descent and landing. The onboard flight computer can use the 3-D map of terrain to guide the vehicle to a safe site. The capabilities of Flash Lidar technology were evaluated through a series of static tests using a calibrated target and through dynamic tests aboard a helicopter and a fixed wing aircraft. The aircraft flight tests were performed over Moon-like terrain in the California and Nevada deserts. This paper briefly describes the Flash Lidar static and aircraft flight test results. These test results are analyzed against the landing application requirements to identify the areas of technology improvement. The ongoing technology advancement activities are then explained and their goals are described.

Amzajerdian, Farzin↗

Processing of 3-Dimensional Flash Lidar Terrain Images Generated From an Airborne Platform

Data from the first Flight Test of the NASA Langley Flash Lidar system have been processed. Results of the analyses are presented and discussed. A digital elevation map of the test site is derived from the data, and is compared with the actual topography. The set of algorithms employed, starting from the initial data sorting, and continuing through to the final digital map classification is described. The accuracy, precision, and the spatial and angular resolution of the method are discussed.

Bulyshev, Alexander↗