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Lidar Sensors for Autonomous Landing and Hazard Avoidance

Lidar technology will play an important role in enabling highly ambitious missions being envisioned for exploration of solar system bodies. Currently, NASA is developing a set of advanced lidar sensors, under the Autonomous Landing and Hazard Avoidance (ALHAT) project, aimed at safe landing of robotic and manned vehicles at designated sites with a high degree of precision. These lidar sensors are an Imaging Flash Lidar capable of generating high resolution three-dimensional elevation maps of the terrain, a Doppler Lidar for providing precision vehicle velocity and altitude, and a Laser Altimeter for measuring distance to the ground and ground contours from high altitudes. The capabilities of these lidar sensors have been demonstrated through four helicopter and one fixed-wing aircraft flight test campaigns conducted from 2008 through 2012 during different phases of their development. Recently, prototype versions of these landing lidars have been completed for integration into a rocket-powered terrestrial free-flyer vehicle (Morpheus) being built by NASA Johnson Space Center. Operating in closed-loop with other ALHAT avionics, the viability of the lidars for future landing missions will be demonstrated. This paper describes the ALHAT lidar sensors and assesses their capabilities and impacts on future landing missions.

Amzajerdian, Farzin

Frequency-Range Distribution of Boulders Around Cone Crater: Relevance to Landing Site Hazard Avoidance

Boulders represent a landing hazard that must be addressed in the planning of future landings on the Moon. A boulder under a landing leg can contribute to deck tilt and boulders can damage spacecraft during landing. Using orbital data to characterize boulder populations at locations where landers have safely touched down (Apollo, Luna, Surveyor, and Chang'e-3 sites) is important for determining landing hazard criteria for future missions. Additionally, assessing the distribution of boulders can address broader science issues, e.g., how far craters distribute boulders and how this distribution varies as a function of crater size and age. The availability of new Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images [1] enables the use of boulder size- and range frequency distributions for a variety of purposes [2-6]. Boulders degrade over time and primarily occur around young or fresh craters that are large enough to excavate bedrock. Here we use NAC images to analyze boulder distributions around Cone crater (340 m diameter) at the Apollo 14 site. Cone crater (CC) was selected because it is the largest crater where astronaut surface photography is available for a radial traverse to the rim. Cone crater is young (approximately 29 Ma [7]) relative to the time required to break down boulders [3,8], giving us a data point for boulder range-frequency distributions (BRFDs) as a function of crater age.

Clegg-Watkins, R. N.

Performance of Flash Lidar with Real-time Image Enhancement Algorithm for Landing Hazard Avoidance

Performance of a 3-D imaging flash lidar employing a novel super-resolution algorithm is characterized by a series of static and dynamic tests. A gantry test of this lidar in which the lidar was placed in an instrumented moving basket above a calibrated hazard field proved an excellent demonstration of hazard avoidance capabilities. Results of the gantry test are reported and potential of flash lidar utilizing super-resolution algorithm for future landing missions are explained.

Hazard Detection

POST2 End-To-End Descent and Landing Simulation for the Autonomous Landing and Hazard Avoidance Technology Project

The Program to Optimize Simulated Trajectories II (POST2) is used as a basis for an end-to-end descent and landing trajectory simulation that is essential in determining the design and performance capability of lunar descent and landing system models and lunar environment models for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project. This POST2-based ALHAT simulation provides descent and landing simulation capability by integrating lunar environment and lander system models (including terrain, sensor, guidance, navigation, and control models), along with the data necessary to design and operate a landing system for robotic, human, and cargo lunar-landing success. This paper presents the current and planned development and model validation of the POST2-based end-to-end trajectory simulation used for the testing, performance and evaluation of ALHAT project system and models.

Fisher, Jody l.

Mars rover local navigation and hazard avoidance

A Mars rover sample return mission has been proposed for the late 1990's. Due to the long speed-of-light delays between earth and Mars, some autonomy on the rover is highly desirable. JPL has been conducting research in two possible modes of rover operation, Computer-Aided Remote Driving and Semiautonomous Navigation. A recently-completed research program used a half-scale testbed vehicle to explore several of the concepts in semiautonomous navigation. A new, full-scale vehicle with all computational and power resources on-board will be used in the coming year to demonstrate relatively fast semiautonomous navigation. The computational and power requirements for Mars rover local navigation and hazard avoidance are discussed.

Wilcox, B. H.

Synopsis of Precision Landing and Hazard Avoidance (PL&HA) Capabilities for Space Exploration

Until recently, robotic exploration missions to the Moon, Mars, and other solar system bodies relied upon controlled blind landings. Because terrestrial techniques for terrain relative navigation (TRN) had not yet been evolved to support space exploration, landing dispersions were driven by the capabilities of inertial navigation systems combined with surface relative altimetry and velocimetry. Lacking tight control over the actual landing location, mission success depended on the statistical vetting of candidate landing areas within the predicted landing dispersion ellipse based on orbital reconnaissance data, combined with the ability of the spacecraft to execute a controlled landing in terms of touchdown attitude, attitude rates, and velocity. In addition, the sensors, algorithms, and processing technologies required to perform autonomous hazard detection and avoidance in real time during the landing sequence were not yet available. Over the past decade, NASA has invested substantial resources on the development, integration, and testing of autonomous precision landing and hazard avoidance (PL&HA) capabilities. In addition to substantially improving landing accuracy and safety, these autonomous PL&HA functions also offer access to targets of interest located within more rugged and hazardous terrain. Optical TRN systems are baselined on upcoming robotic landing missions to the Moon and Mars, and NASA JPL is investigating the development of a comprehensive PL&HA system for a Europa lander. These robotic missions will demonstrate and mature PL&HA technologies that are considered essential for future human exploration missions. PL&HA technologies also have applications to rendezvous and docking/berthing with other spacecraft, as well as proximity navigation, contact, and retrieval missions to smaller bodies with microgravity environments, such as asteroids.

Robertson, Edward A.

Performance Analysis of A Dual Quaternion Guidance Algorithm Applicable During Lunar Approach With A Hazard Avoidance Maneuver

There is currently a need for advanced guidance and targeting algorithms that can provide real-time trajectories in the presence of state and vehicle constraints during powered descent. The Safe & Precise Landing Integrated Capabilities Evolution (SPLICE) program aims to mature Hazard Detection (HD) technology along with advanced navigation and guidance algorithms. This paper will report the overall performance of the SPLICE Dual Quaternion Guidance (DQG) algorithm which is a 6-Degree-of-Freedom (6-DOF) convex optimization-based guidance algorithm that can enforce multiple vehicle and state constraints required for Hazard Detection Lidar (HDL) scans during the approach phase. DQG was tested in a closed-loop lunar descent simulation with realistic HDL sensing constraints in a Monte Carlo assessment of 1000 dispersed runs.

Guidance

Planetary Rover local navigation and hazard avoidance

A Planetary Rover will have to be able to navigate through its local environment autonomously, due to communication delays. This implies that the vehicle must be able to sense its environment, plan a course through that environment, and react appropriately to unexpected situations as they appear. All this must be done while guiding the vehicle toward the goals that have been given to it from its operators on the earth. This paper describes research at the Jet Propulsion Laboratory which concentrates on the sensing, perception, planning and execution monitoring that must be carried out by the rover to ensure that a safe and efficient path is found by the rover, and that that path is performed correctly.

Miller, David P.

High Resolution Terrain Sensing Lidar for Precision Navigation and Safe Landing of Space and Aerial Vehicles

A 3-D imaging flash lidar sensor employing a resolution enhancement algorithm is being developed at NASA Langley Research Center for providing Terrain Relative Navigation and Hazard Avoidance capabilities onboard spacecraft landing on the Moon, Mars, and other planetary bodies. This lidar sensor, we refer to as Terrain Sensing Lidar (TSL), is a solution for future missions that require landing at pre-designated sites near high value resources or at areas of high scientific value, while avoiding hazardous terrain features, such as escarpments, craters, slopes, and rocks, or pre-deployed assets. TSL can also benefit terrestrial applications such as autonomous aerial vehicles without reliance on signals from Global Positioning System (GPS). The feasibility of the TSL concept has been shown through a series of drone, fixed-wing aircraft, and helicopter flight tests. A prototype version of the TSL has been recently assembled for conducting another set of flight tests to demonstrate its readiness for upcoming landing missions. This paper describes the TSL, provides its performance parameters, and explains its operational concepts for landing missions.

Precision Navigation

The Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT)

As NASA plans to send humans back to the Moon and develop a lunar outpost, technologies must be developed to place humans and cargo safely, precisely, repeatedly, on the lunar surface with the capability to avoid surface hazards. Exploration Space Architecture Study requirements include the need for global lunar surface access with safe, precise landing without lighting constraints on terrain that may have landing hazards for human scale landing vehicles. Landing accuracies of perhaps 1,000 meters for sortie crew missions to 10 s of meters for Outpost class missions are required. The Autonomous precision Landing Hazard Avoidance Technology (ALHAT) project will develop the new and unique descent and landing Guidance, Navigation and Control (GNC) hardware and software technologies necessary for these capabilities. The ALHAT project will qualify a lunar descent and landing GNC system to a Technology Readiness Level (TRL) of 6 capable of supporting lunar crewed, cargo, and robotic missions. The (ALHAT) development project was chartered by NASA Headquarters in October 2006. The initial effort to write a project plan and define an ALHAT Team was followed by a fairly aggressive research and analysis effort to determine what technologies existed that could be developed and applied to the lunar landing problems indicated above. This paper describes the project development, research, analysis and concept evolution that has occurred since the assignment of the project. This includes the areas of systems engineering, GNC, sensors, sensor algorithms, simulations, fielding testing, laboratory testing, Hardware-In-The-Loop testing, system avionics and system certification concepts.

Epp, Chirold D.