ALBERT

Description: Since 2011, the Autonomous Descent and Ascent Powered-Flight Testbed (ADAPT) has been used to demonstrate advanced descent and landing technologies onboard the Masten Space Systems (MSS) Xombie vertical-takeoff, vertical-landing suborbital rocket. The current instantiation of ADAPT is a stand-alone payload comprising sensing and avionics for terrain-relative navigation and fuel-optimal onboard planning of large divert trajectories, thus providing complete pin-point landing capabilities needed for planetary landers. To this end, ADAPT combines two technologies developed at JPL, the Lander Vision System (LVS), and the Guidance for Fuel Optimal Large Diverts (G-FOLD) software. This paper describes the integration and testing of LVS and G-FOLD in the ADAPT payload, culminating in two successful free flight demonstrations on the Xombie vehicle conducted in December 2014.

Description: In this paper, we discuss steps towards the development of an autonomy architecture, and concentrate on the autonomous flight control subsystem.

Description: Robotic lighter-than-air vehicles, or aerobots, provide a strategic platform for the exploration of planets and moons with an atmosphere, such as Venus, Mars, Titan and the gas giants.

Description: Robotic lighter-than-air vehicles, or aerobots, provide strategic platform for the exploration of planets and moons with an atmosphere, such as Venus, Mars, Titan and the gas giants. In this paper, we discuss steps towards the development of an autonomy architecture, and concentrate on the autonomous fight control subsystem.

Description: The Mars Science Laboratory (MSL) will deliver a 900 kg rover to the surface of Mars in August 2012. MSL will utilize a new pulse-Doppler landing radar, the Terminal Descent Sensor (TDS). The TDS employs six narrow-beam antennas to provide unprecedented slant range and velocity performance at Mars to enable soft touchdown of the MSL rover using a unique sky crane Entry, De-scent, and Landing (EDL) technique. Prior to use on MSL, the TDS was put through a rigorous verification and validation (V&V) process. A key element of this V&V was operating the TDS over a series of field tests, using flight-like profiles expected during the descent and landing of MSL over Mars-like terrain on Earth. Limits of TDS performance were characterized with additional testing meant to stress operational modes outside of the expected EDL flight profiles. The flight envelope over which the TDS must operate on Mars encompasses such a large range of altitudes and velocities that a variety of venues were neces-sary to cover the test space. These venues included an F/A-18 high performance aircraft, a Eurocopter AS350 AStar helicopter and 100-meter tall Echo Towers at the China Lake Naval Air Warfare Center. Testing was carried out over a five year period from July 2006 to June 2011. TDS performance was shown, in gen-eral, to be excellent over all venues. This paper describes the planning, design, and implementation of the field test campaign plus results and lessons learned.

Description: The Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project is developing a system for safe and precise manned lunar landing that involves novel sensors, but also specific algorithms. ALHAT has selected imaging LIDAR (light detection and ranging) as the sensing modality for onboard hazard detection because imaging LIDARs can rapidly generate direct measurements of the lunar surface elevation from high altitude. Then, starting with the LIDAR-based Hazard Detection and Avoidance (HDA) algorithm developed for Mars Landing, JPL has developed a mature set of HDA software for the manned lunar landing problem. Landing hazards exist everywhere on the Moon, and many of the more desirable landing sites are near the most hazardous terrain, so HDA is needed to autonomously and safely land payloads over much of the lunar surface. The HDA requirements used in the ALHAT project are to detect hazards that are 0.3 m tall or higher and slopes that are 5 or greater. Steep slopes, rocks, cliffs, and gullies are all hazards for landing and, by computing the local slope and roughness in an elevation map, all of these hazards can be detected. The algorithm in this innovation is used to measure slope and roughness hazards. In addition to detecting these hazards, the HDA capability also is able to find a safe landing site free of these hazards for a lunar lander with diameter .15 m over most of the lunar surface. This software includes an implementation of the HDA algorithm, software for generating simulated lunar terrain maps for testing, hazard detection performance analysis tools, and associated documentation. The HDA software has been deployed to Langley Research Center and integrated into the POST II Monte Carlo simulation environment. The high-fidelity Monte Carlo simulations determine the required ground spacing between LIDAR samples (ground sample distances) and the noise on the LIDAR range measurement. This simulation has also been used to determine the effect of viewing on hazard detection performance. The software has also been deployed to Johnson Space Center and integrated into the ALHAT real-time Hardware-in-the-Loop testbed.

Description: An architecture for autonomous operation of an aerobot (i.e., a robotic blimp) to be used in scientific exploration of planets and moons in the Solar system with an atmosphere (such as Titan and Venus) is undergoing development. This architecture is also applicable to autonomous airships that could be flown in the terrestrial atmosphere for scientific exploration, military reconnaissance and surveillance, and as radio-communication relay stations in disaster areas. The architecture was conceived to satisfy requirements to perform the following functions: a) Vehicle safing, that is, ensuring the integrity of the aerobot during its entire mission, including during extended communication blackouts. b) Accurate and robust autonomous flight control during operation in diverse modes, including launch, deployment of scientific instruments, long traverses, hovering or station-keeping, and maneuvers for touch-and-go surface sampling. c) Mapping and self-localization in the absence of a global positioning system. d) Advanced recognition of hazards and targets in conjunction with tracking of, and visual servoing toward, targets, all to enable the aerobot to detect and avoid atmospheric and topographic hazards and to identify, home in on, and hover over predefined terrain features or other targets of scientific interest. The architecture is an integrated combination of systems for accurate and robust vehicle and flight trajectory control; estimation of the state of the aerobot; perception-based detection and avoidance of hazards; monitoring of the integrity and functionality ("health") of the aerobot; reflexive safing actions; multi-modal localization and mapping; autonomous planning and execution of scientific observations; and long-range planning and monitoring of the mission of the aerobot. The prototype JPL aerobot (see figure) has been tested extensively in various areas in the California Mojave desert.

Description: Landing hazard detection and avoidance technology is being pursued within NASA to improve landing safety and increase access to sites of interest on the lunar surface. The performance of a hazard detection and avoidance system depends on properties of the terrain, sensor performance, algorithm design, vehicle characteristics and the overall all guidance navigation and control architecture. This paper analyzes the size of the region that must be imaged, sensor performance parameters and the impact of trajectory angle on hazard detection performance. The analysis shows that vehicle hazard tolerance is the driving parameter for hazard detection system design.

Description: The driving precision landing requirement for the Autonomous Landing and Hazard Avoidance Technology project is to autonomously land within 100m of a predetermined location on the lunar surface. Traditional lunar landing approaches based on inertial sensing do not have the navigational precision to meet this requirement. The purpose of Terrain Relative Navigation (TRN) is to augment inertial navigation by providing position or bearing measurements relative to known surface landmarks. From these measurements, the navigational precision can be reduced to a level that meets the 100m requirement. There are three different TRN functions: global position estimation, local position estimation and velocity estimation. These functions can be achieved with active range sensing or passive imaging. This paper gives a survey of many TRN approaches and then presents some high fidelity simulation results for contour matching and area correlation approaches to TRN using active sensors. Since TRN requires an a-priori reference map, the paper concludes by describing past and future lunar imaging and digital elevation map data sets available for this purpose.

Description: The Huygens probe arrived at Saturn's moon Titan on January 14, 2005, unveiling a world that is radically different from any other in the Solar system. The data obtained, complemented by continuing observations from the Cassini spacecraft, show methane lakes, river channels and drainage basins, sand dunes, cryovolcanos and sierras. This has lead to an enormous scientific interest in a follow-up mission to Titan, using a robotic lighter-than-air vehicle (or aerobot). Aerobots have modest power requirements, can fly missions with extended durations, and have very long distance traverse capabilities. They can execute regional surveys, transport and deploy scientific instruments and in-situ laboratory facilities over vast distances, and also provide surface sampling at strategic science sites. This paper describes our progress in the development of the autonomy technologies that will be required for exploration of Titan. We provide an overview of the autonomy architecture and some of its key components. We also show results obtained from autonomous flight tests conducted in the Mojave desert.