LUNAR AND PLANETARY SOFT LANDINGS BY MEANS OF GAS-FILLED BALLOONS
Lunar and planetary soft landings by gas-filled balloons
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Lunar and planetary soft landings by gas-filled balloons
The ability of lidar technology to provide three-dimensional elevation maps of the terrain, high precision distance to the ground, and approach velocity can enable safe landing of robotic and manned vehicles with a high degree of precision. Currently, NASA is developing novel lidar sensors aimed at needs of future planetary landing missions. These lidar sensors are a 3-Dimensional Imaging Flash Lidar, a Doppler Lidar, and a Laser Altimeter. The Flash Lidar is capable of generating elevation maps of the terrain that indicate hazardous features such as rocks, craters, and steep slopes. The elevation maps collected during the approach phase of a landing vehicle, at about 1 km above the ground, can be used to determine the most suitable safe landing site. The Doppler Lidar provides highly accurate ground relative velocity and distance data allowing for precision navigation to the landing site. Our Doppler lidar utilizes three laser beams pointed to different directions to measure line of sight velocities and ranges to the ground from altitudes of over 2 km. Throughout the landing trajectory starting at altitudes of about 20 km, the Laser Altimeter can provide very accurate ground relative altitude measurements that are used to improve the vehicle position knowledge obtained from the vehicle navigation system. At altitudes from approximately 15 km to 10 km, either the Laser Altimeter or the Flash Lidar can be used to generate contour maps of the terrain, identifying known surface features such as craters, to perform Terrain relative Navigation thus further reducing the vehicle s relative position error. This paper describes the operational capabilities of each lidar sensor and provides a status of their development. Keywords: Laser Remote Sensing, Laser Radar, Doppler Lidar, Flash Lidar, 3-D Imaging, Laser Altimeter, Precession Landing, Hazard Detection
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.
Planetary landers need to reduce velocity at low altitude for soft landing. Traditionally, estimating velocity and altitude has been performed with radar sensors whose performance meets the specific mission needs. There are not very many options for these sensors and they are difficult to include in a flight system either due to obsolescence, prohibitive cost or difficulty in accommodation. Recently, alternative sensing modalities are being pursued including Doppler LiDAR and vision. This paper describes results from a recent helicopter field test of a binocular stereo vision system for deorbit descent and landing applications. The system consisted of two 18.6 ̊ field of view cameras mounted 1.7m apart. Post processing of the images showed ranging accuracy better than 1% up to 500mand 17 cm/s velocimetry accuracy at 37m. For a flight system these images could be input into an FPGA-based processor which processes dense stereo and visual odometry in less than 1 second to achieve the stereo ranging frame rates required for soft landing. When coupled with vision based Terrain Relative Navigation this stereo system enables landing accuracies on the order of 10m.
Dynamic analysis and development of response histories and tradeoff study charts for spherical impact limiters for protecting hard landing planetary payloads
An enhanced algorithm is developed that builds on a previous innovation of fuel-optimal powered-descent guidance (PDG) for planetary pinpoint landing. The PDG problem is to compute constrained, fuel-optimal trajectories to land a craft at a prescribed target on a planetary surface, starting from a parachute cut-off point and using a throttleable descent engine. The previous innovation showed the minimal-fuel PDG problem can be posed as a convex optimization problem, in particular, as a Second-Order Cone Program, which can be solved to global optimality with deterministic convergence properties, and hence is a candidate for onboard implementation. To increase the speed and robustness of this convex PDG algorithm for possible onboard implementation, the following enhancements are incorporated: 1) Fast detection of infeasibility (i.e., control authority is not sufficient for soft-landing) for subsequent fault response. 2) The use of a piecewise-linear control parameterization, providing smooth solution trajectories and increasing computational efficiency. 3) An enhanced line-search algorithm for optimal time-of-flight, providing quicker convergence and bounding the number of path-planning iterations needed. 4) An additional constraint that analytically guarantees inter-sample satisfaction of glide-slope and non-sub-surface flight constraints, allowing larger discretizations and, hence, faster optimization. 5) Explicit incorporation of Mars rotation rate into the trajectory computation for improved targeting accuracy. These enhancements allow faster convergence to the fuel-optimal solution and, more importantly, remove the need for a "human-in-the-loop," as constraints will be satisfied over the entire path-planning interval independent of step-size (as opposed to just at the discrete time points) and infeasible initial conditions are immediately detected. Finally, while the PDG stage is typically only a few minutes, ignoring the rotation rate of Mars can introduce 10s of meters of error. By incorporating it, the enhanced PDG algorithm becomes capable of pinpoint targeting.
This handbook describes a two-semester senior design course sponsored by the NASA Office of Education, the Exploration Systems Mission Directorate (ESMD), and the NASA Space Grant Consortium. The course was developed and implemented by the Mechanical and Aerospace Engineering Department (MAE) at Utah State University. The course final outcome is a packaged senior design course that can be readily incorporated into the instructional curriculum at universities across the country. The course materials adhere to the standards of the Accreditation Board for Engineering and Technology (ABET), and is constructed to be relevant to key research areas identified by ESMD. The design project challenged students to apply systems engineering concepts to define research and training requirements for a terrestrial-based lunar landing simulator. This project developed a flying prototype for a Lunar or Planetary Surface Landing Research Vehicle (LPSRV). Per NASA specifications the concept accounts for reduced lunar gravity, and allows the terminal stage of lunar descent to be flown either by remote pilot or autonomously. This free-flying platform was designed to be sufficiently-flexible to allow both sensor evaluation and pilot training. This handbook outlines the course materials, describes the systems engineering processes developed to facilitate design fabrication, integration, and testing. This handbook presents sufficient details of the final design configuration to allow an independent group to reproduce the design. The design evolution and details regarding the verification testing used to characterize the system are presented in a separate project final design report. Details of the experimental apparatus used for system characterization may be found in Appendix F, G, and I of that report. A brief summary of the ground testing and systems verification is also included in Appendix A of this report. Details of the flight tests will be documented in a separate flight test report. This flight test report serves as a complement to the course handbook presented here. This project was extremely ambitious, and achieving all of the design and test objectives was a daunting task. The schedule ran slightly longer than a single academic year with the complete design closure not occurring until early April. Integration and verification testing spilled over into late May and the first flight did not occur until mid to late June. The academic year at Utah State University ended on May 8, 2010. Following the end of the academic year, testing and integration was performed by the faculty advisor, paid research assistants, and volunteer student help
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Global Positioning System (GPS) is commonly used in terrestrial navigation for vehicle position and velocity knowledge. In the absence of a GPS signal, past landing missions to planetary bodies primarily relied on radar to provide the necessary data to execute descent and landing maneuvers. We have developed a coherent Doppler lidar, called Navigation Doppler Lidar (NDL), that offers several critical advantages com-pared to radar, including significantly higher precision with reduced size, mass, and power.
The ALHAT project was chartered by NASA HQ in 2006 to develop and mature to TRL 6 an autonomous lunar landing GN&C and sensing system for crewed, cargo, and robotic planetary landing vehicles. The multi-center ALHAT team was tasked with providing a system capable of identifying and avoiding surface hazards in real time to enable safe precision landing to within tens of meters of a designated planetary landing site under any lighting conditions.
A coherent Doppler lidar has been developed by NASA for providing vector velocity and altitude data to landing vehicles. Future robotic and manned missions to planetary bodies demand precise ground-relative velocity and altitude data to execute complex descent maneuvers for safe, soft and pinpoint landing at a pre-designated site. Operating from over five kilometers altitude, this lidar provides velocity and range data within a few cm/sec and a few meters precision, respectively, depending on the vehicle dynamics. Two upcoming lunar landing missions will serve as the technology demonstration for robotic and manned landing missions to the Moon, Mars, and other solar system destinations. This paper describes the lidar design and its expected performance on landing vehicles.
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.
Lidar has been identified by NASA as a key technology for enabling autonomous safe landing of future robotic and crewed lunar landing vehicles. NASA LaRC has been developing three laser/lidar sensor systems under the ALHAT project. The capabilities of these Lidar sensor systems were evaluated through a series of static tests using a calibrated target and through dynamic tests aboard helicopters and a fixed wing aircraft. The airborne tests were performed over Moon-like terrain in the California and Nevada deserts. These tests provided the necessary data for the development of signal processing software, and algorithms for hazard detection and navigation. The tests helped identify technology areas needing improvement and will also help guide future technology advancement activities.
Missions to solar system bodies must meet increasingly ambitious objectives requiring highly reliable “precision landing”, and “hazard avoidance” capabilities. To meet these needs, we have developed two lidar sensor systems that can be used individually or in concert depending on the mission requirements. One is Navigation Doppler Lidar (NDL) capable of providing vehicle precision vector velocity and ground-relative altitude and the other is an Imaging Flash Lidar for Terrain Relative Navigation and Hazard Detection and Avoidance. Using both lidar sensors together will enable landing anywhere and under any lighting condition. The NDL performance has been extensively characterized through numerous ground and aircraft flight tests and will be soon demonstrated on two lunar landing missions (mid-2023). The Flash Lidar performance is currently being assessed onboard a drone and will soon be tested on helicopter and fixed-wing aircraft platforms. This paper describes both lidar sensors and their expected operation on landing vehicles.
The Autonomous Landing Hazard Avoidance Technology (ALHAT) Project is chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. The ALHAT System must be capable of identifying and avoiding surface hazards to enable a safe and accurate landing to within tens of meters of designated and certified landing sites anywhere on a planetary surface under any lighting conditions. Since its inception in 2006, the ALHAT Project has executed four field test campaigns to characterize and mature sensors and algorithms that support real-time hazard detection and global/local precision navigation for planetary landings. The driving objective for Government Fiscal Year 2012 (GFY2012) is to successfully demonstrate autonomous, real-time, closed loop operation of the ALHAT system in a realistic free flight scenario on Earth using the Morpheus lander developed at the Johnson Space Center (JSC). This goal represents an aggressive target consistent with a lean engineering culture of rapid prototyping and development. This culture is characterized by prioritizing early implementation to gain practical lessons learned and then building on this knowledge with subsequent prototyping design cycles of increasing complexity culminating in the implementation of the baseline design. This paper provides an overview of the ALHAT/Morpheus flight demonstration activities in GFY2012, including accomplishments, current status, results, and lessons learned. The ALHAT/Morpheus effort is also described in the context of a technology path in support of future crewed and robotic planetary exploration missions based upon the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN).
Coherent lidar can play a critical role in future planetary exploration missions by providing key guidance, navigation, and control (GNC) data necessary for navigating planetary landers to the pre-selected site and achieving autonomous safe soft-landing. Although the landing accuracy has steadily improved over time to approximately 35 km for the recent Mars Exploration Rovers due to better approach navigation, a drastically different guidance, navigation and control concept is required to meet future mission requirements. For example, future rovers will require better than 6 km landing accuracy for Mars and better than 1 km for the Moon plus maneuvering capability to avoid hazardous terrain features. For this purpose, an all-fiber coherent lidar is being developed to address the call for advancement of entry, descent, and landing technologies. This lidar will be capable of providing precision range to the ground and approach velocity data, and in the case of landing on Mars, it will also measure the atmospheric wind and density. The lidar obtains high resolution range information from a frequency modulated-continuous wave (FM-CW) laser beam whose instantaneous frequency varies linearly with time, and the ground vector velocity is directly extracted from the Doppler frequency shift. Utilizing the high concentration of aerosols in the Mars atmosphere (approx. two order of magnitude higher than the Earth), the lidar can measure wind velocity with a few watts of optical power. Operating in 1.57 micron wavelength regime, the lidar can use the differential absorption (DIAL) technique to measure the average CO2 concentration along the laser beam using, that is directly proportional to the Martian atmospheric density. Employing fiber optics components allows for the lidar multi-functional operation while facilitating a highly efficient, compact and reliable design suitable for integration into a spacecraft with limited mass, size, and power resources.
A Flash Lidar utilizing a novel Super-Resolution technique has been developed for providing Terrain Relative Navigation and Hazard Avoidance capabilities onboard landing vehicles.
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