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Intelligent Autonomy for Unmanned Surface and Underwater Vehicles

As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decisionmaking, which would otherwise be performed by humanoperators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented.

environmental sensing↗

Rocket Sled Propelled Testing of a Supersonic Inflatable Aerodynamic Decelerator

Decelerators (IADs) have traditionally been tested in wind tunnels. As the limitations of these test facilities are reached, other avenues must be pursued. The IAD being tested is a Supersonic IAD (SIAD), which attaches just aft of the heatshield around the perimeter of an entry body. This 'attached torus' SIAD is meant to improve the accuracy of landing for robotic class missions to Mars and allow for potentially increased payloads. The SIAD Design Verification (SDV) test aims to qualify the SIAD by applying a targeted aerodynamic load to the vehicle. While many test architectures were researched, a rocket sled track was ultimately chosen to be the most cost effective way to achieve the desired dynamic pressures. The Supersonic Naval Ordnance Research Track (SNORT) at the Naval Air Warfare Center Weapons Division (NAWCWD) China Lake is a four mile test track, traditionally used for warhead and ejection seat testing. Prior to SDV, inflatable drag bodies have been tested on this particular track. Teams at Jet Propulsion Laboratory (JPL) and NAWCWD collaborate together to design and fabricate one of the largest sleds ever built. The SDV sled is comprised of three individual sleds: a Pusher Sled which holds the solid booster rockets, an Item Sled which supports the test vehicle, and a Camera Sled that is pushed in front for in-situ footage and measurements. The JPL-designed Test Vehicle has a full-scale heatshield shape and contains all instrumentation and inflation systems necessary to inflate and test a SIAD. The first campaign that is run at SNORT tested all hardware and instrumentation before the SIAD was ready to be tested. For each of the three tests in this campaign, the number of rockets and top speed was increased and the data analyzed to ensure the hardware is safe at the necessary accelerations and aerodynamic loads.

Supersonic Inflatable Aerodynamic Decelerators (SI↗

Real-Time and High-Fidelity Simulation Environment for Autonomous Ground Vehicle Dynamics

This paper reports on a collaborative project between U.S. Army TARDEC and Jet Propulsion Laboratory (JPL) to develop a unmanned ground vehicle (UGV) simulation model using the ROAMS vehicle modeling framework. Besides modeling the physical suspension of the vehicle, the sensing and navigation of the HMMWV vehicle are simulated. Using models of urban and off-road environments, the HMMWV simulation was tested in several ways, including navigation in an urban environment with obstacle avoidance and the performance of a lane change maneuver.

vehicle sensing↗

SMAP Radar Processing and Calibration

The Soil Moisture Active Passive (SMAP) mission is part of the NASA space-based Earth observation program, and consists of an L-band radar and radiometer scheduled for launch into sun synchronous orbit in late 2014. A joint effort of the Jet Propulsion Laboratory (JPL) and the Goddard Space Flight Center (GSFC), the SMAP mission draws heavily on the design and risk reduction heritage of the Hydrosphere State (Hydros) mission [1], [2]. The SMAP science and applications objectives are to: 1) understand processes that link the terrestrial water, energy and carbon cycles, 2) estimate global water and energy fluxes at the land surface, 3) quantify net carbon flux in boreal landscapes, 4) enhance weather and climate forecast skill, and 5) develop improved flood prediction and drought monitoring capability. To meet these science objectives, SMAP ground processing will combine the attributes of the radar and radiometer observations (in terms of their spatial resolution and sensitivity to soil moisture, surface roughness, and vegetation) to estimate soil moisture with 4% volumetric accuracy at a resolution of 10 km, and freeze-thaw state at a resolution of 1-3 km. Model sensitivities translate the soil moisture accuracy to a radar backscatter accuracy of 1 dB (1 sigma) at 3 km resolution and a brightness temperature accuracy of 1.3 K at 40 km resolution. This paper will describe the level 1 radar processing and calibration challenges and the choices made so far for the algorithms and software implementation.

Synthetic Aperture Radar (SAR),↗

Space Mission Concept Development Using Concept Maturity Levels

Over the past five years, pre-project formulation experts at the Jet Propulsion Laboratory (JPL) has developed and implemented a method for measuring and communicating the maturity of space mission concepts. Mission concept development teams use this method, and associated tools, prior to concepts entering their Formulation Phases (Phase A/B). The organizing structure is Concept Maturity Level (CML), which is a classification system for characterizing the various levels of a concept's maturity. The key strength of CMLs is the ability to evolve mission concepts guided by an incremental set of assessment needs. The CML definitions have been expanded into a matrix form to identify the breadth and depth of analysis needed for a concept to reach a specific level of maturity. This matrix enables improved assessment and communication by addressing the fundamental dimensions (e.g., science objectives, mission design, technical risk, project organization, cost, export compliance, etc.) associated with mission concept evolution. JPL's collaborative engineering, dedicated concept development, and proposal teams all use these and other CML-appropriate design tools to advance their mission concept designs. This paper focuses on mission concept's early Pre-Phase A represented by CMLs 1- 4. The scope was limited due to the fact that CMLs 5 and 6 are already well defined based on the requirements documented in specific Announcement of Opportunities (AO) and Concept Study Report (CSR) guidelines, respectively, for competitive missions; and by NASA's Procedural Requirements NPR 7120.5E document for Projects in their Formulation Phase.

Concept Maturity Levels (CMLs)↗

Near-Earth Asteroid Retrieval Mission (ARM) Study

The Asteroid Redirect Mission (ARM) concept brings together the capabilities of the science, technology, and the human exploration communities on a grand challenge combining robotic and human space exploration beyond low Earth orbit. This paper addresses the key aspects of this concept and the options studied to assess its technical feasibility. Included are evaluations of the expected number of potential targets, their expected discovery rate, the necessity to adequately characterize candidate mission targets, the process to capture a non-cooperative asteroid in deep space, and the power and propulsion technology required for transportation back to the Earth-Moon system. Viable options for spacecraft and mission designs are developed. Orbits for storing the retrieved asteroid that are stable for more than a hundred years, yet allow for human exploration and commercial utilization of a redirected asteroid, are identified. The study concludes that the key aspects of finding, capturing and redirecting an entire small, near-Earth asteroid to the Earth-Moon system by the first half of the next decade are technically feasible. The study was conducted from January 2013 through March 2013 by the Jet Propulsion Laboratory (JPL) in collaboration with Glenn Research Center (GRC), Johnson Space Center (JSC), Langley Research Center (LaRC), and Marshall Space Flight Center (MSFC).

Solar Electric Propulsion (SEP)↗

Real-Time and High-Fidelity Simulation Environment for Autonomous Ground Vehicle Dynamics

This paper reports on a collaborative project between U.S. Army TARDEC and Jet Propulsion Laboratory (JPL) to develop a unmanned ground vehicle (UGV) simulation model using the ROAMS vehicle modeling framework. Besides modeling the physical suspension of the vehicle, the sensing and navigation of the HMMWV vehicle are simulated. Using models of urban and off-road environments, the HMMWV simulation was tested in several ways, including navigation in an urban environment with obstacle avoidance and the performance of a lane change maneuver.

unmanned ground vehicle (UGV)↗

Comparison of Simulated Contrast Performance of Different Phase Induced Amplitude Apodization (PIAA) Coronagraph Configurations

We compare the broadband contrast performances of several Phase Induced Amplitude Apodization (PIAA) coronagraph configurations through modeling and simulations. The basic optical design of the PIAA coronagraph is the same as NASA's High Contrast Imaging Testbed (HCIT) setup at the Jet Propulsion Laboratory (JPL). Using a deformable mirror and a broadband wavefront sensing and control algorithm, we create a "dark hole" in the broadband point-spread function (PSF) with an inner working angle (IWA) of 2(f lambda/D)(sub sky). We evaluate two systems in parallel. One is a perfect system having a design PIAA output amplitude and not having any wavefront error at its exit-pupil. The other is a realistic system having a design PIAA output amplitude and the measured residual wavefront error. We also investigate the effect of Lyot stops of various sizes when a postapodizer is and is not present. Our simulations show that the best 7.5%-broadband contrast value achievable with the current PIAA coronagraph is approximately 1.5x10(exp -8).

adaptive optics↗

Fault Management Architectures and the Challenges of Providing Software Assurance

The satellite systems Fault Management (FM) is focused on safety, the preservation of assets, and maintaining the desired functionality of the system. How FM is implemented varies among missions. Common to most is system complexity due to a need to establish a multi-dimensional structure across hardware, software and operations. This structure is necessary to identify and respond to system faults, mitigate technical risks and ensure operational continuity. These architecture, implementation and software assurance efforts increase with mission complexity. Because FM is a systems engineering discipline with a distributed implementation, providing efficient and effective verification and validation (VV) is challenging. A breakout session at the 2012 NASA Independent Verification Validation (IVV) Annual Workshop titled VV of Fault Management: Challenges and Successes exposed these issues in terms of VV for a representative set of architectures. NASA's IVV is funded by NASA's Software Assurance Research Program (SARP) in partnership with NASA's Jet Propulsion Laboratory (JPL) to extend the work performed at the Workshop session. NASA IVV will extract FM architectures across the IVV portfolio and evaluate the data set for robustness, assess visibility for validation and test, and define software assurance methods that could be applied to the various architectures and designs. This work focuses efforts on FM architectures from critical and complex projects within NASA. The identification of particular FM architectures, visibility, and associated VVIVV techniques provides a data set that can enable higher assurance that a satellite system will adequately detect and respond to adverse conditions. Ultimately, results from this activity will be incorporated into the NASA Fault Management Handbook providing dissemination across NASA, other agencies and the satellite community. This paper discusses the approach taken to perform the evaluations and preliminary findings from the research including identification of FM architectures, visibility observations, and methods utilized for VVIVV.

Fault Management↗

A New Blind Pointing Model Improves Large Reflector Antennas Precision Pointing at Ka-Band (32 GHz)

The National Aeronautics and Space Administration (NASA), Jet Propulsion Laboratory (JPL)-Deep Space Network (DSN) subnet of 34-m Beam Waveguide (BWG) Antennas was recently upgraded with Ka-Band (32-GHz) frequency feeds for space research and communication. For normal telemetry tracking a Ka-Band monopulse system is used, which typically yields 1.6-mdeg mean radial error (MRE) pointing accuracy on the 34-m diameter antennas. However, for the monopulse to be able to acquire and lock, for special radio science applications where monopulse cannot be used, or as a back-up for the monopulse, high-precision open-loop blind pointing is required. This paper describes a new 4th order pointing model and calibration technique, which was developed and applied to the DSN 34-m BWG antennas yielding 1.8 to 3.0-mdeg MRE pointing accuracy and amplitude stability of 0.2 dB, at Ka-Band, and successfully used for the CASSINI spacecraft occultation experiment at Saturn and Titan. In addition, the new 4th order pointing model was used during a telemetry experiment at Ka-Band (32 GHz) utilizing the Mars Reconnaissance Orbiter (MRO) spacecraft while at a distance of 0.225 astronomical units (AU) from Earth and communicating with a DSN 34-m BWG antenna at a record high rate of 6-megabits per second (Mb/s).

DSN↗

Stereo Vision Based Terrain Mapping for Off-Road Autonomous Navigation

Successful off-road autonomous navigation by an unmanned ground vehicle (UGV) requires reliable perception and representation of natural terrain. While perception algorithms are used to detect driving hazards, terrain mapping algorithms are used to represent the detected hazards in a world model a UGV can use to plan safe paths. There are two primary ways to detect driving hazards with perception sensors mounted to a UGV: binary obstacle detection and traversability cost analysis. Binary obstacle detectors label terrain as either traversable or non-traversable, whereas, traversability cost analysis assigns a cost to driving over a discrete patch of terrain. In uncluttered environments where the non-obstacle terrain is equally traversable, binary obstacle detection is sufficient. However, in cluttered environments, some form of traversability cost analysis is necessary. The Jet Propulsion Laboratory (JPL) has explored both approaches using stereo vision systems. A set of binary detectors has been implemented that detect positive obstacles, negative obstacles, tree trunks, tree lines, excessive slope, low overhangs, and water bodies. A compact terrain map is built from each frame of stereo images. The mapping algorithm labels cells that contain obstacles as no-go regions, and encodes terrain elevation, terrain classification, terrain roughness, traversability cost, and a confidence value. The single frame maps are merged into a world map where temporal filtering is applied. In previous papers, we have described our perception algorithms that perform binary obstacle detection. In this paper, we summarize the terrain mapping capabilities that JPL has implemented during several UGV programs over the last decade and discuss some challenges to building terrain maps with stereo range data.

passive perception↗

Investigation of Primary Mirror Segment's Residual Errors for the Thirty Meter Telescope

The primary mirror segment aberrations after shape corrections with warping harness have been identified as the single largest error term in the Thirty Meter Telescope (TMT) image quality error budget. In order to better understand the likely errors and how they will impact the telescope performance we have performed detailed simulations. We first generated unwarped primary mirror segment surface shapes that met TMT specifications. Then we used the predicted warping harness influence functions and a Shack-Hartmann wavefront sensor model to determine estimates for the 492 corrected segment surfaces that make up the TMT primary mirror. Surface and control parameters, as well as the number of subapertures were varied to explore the parameter space. The corrected segment shapes were then passed to an optical TMT model built using the Jet Propulsion Laboratory (JPL) developed Modeling and Analysis for Controlled Optical Systems (MACOS) ray-trace simulator. The generated exit pupil wavefront error maps provided RMS wavefront error and image-plane characteristics like the Normalized Point Source Sensitivity (PSSN). The results have been used to optimize the segment shape correction and wavefront sensor designs as well as provide input to the TMT systems engineering error budgets.

warping harness↗

Demonstration of on Sky Contrast Improvement Using the Modified Gerchberg-Saxton Algorithm at the Palomar Observatory

We have successfully demonstrated significant improvements in the high contrast detection limit of the Well-Corrected Subaperture (WCS) using the Autonomous Phase Retrieval Calibration (APRC) software package developed at the Jet Propulsion Laboratory (JPL) for the Palomar adaptive optics instrument (PALAO). APRC utilizes the Modified Gerchberg-Saxton (MGS) wavefront sensing algorithm, also developed at JPL. The WCS delivers such excellent correction of the atmosphere that non-common path (NCP) wavefront errors not sensed by PALAO but present at the coronagraphic image plane begin to factor heavily as a limit to contrast. We have implemented the APRC program to reduce these NCP wavefront errors from 110 nm to 35 nm (rms) in the lab, and we have extended these exceptional results to targets on the sky for the first time, leading to a significant suppression of speckle noise. Consequently we now report a contrast level of very nearly 1x10(exp -4) at separations of 2 lambda/D before the data is post processed. We describe here the major components of our instrument, the work done to improve the NCP wavefront errors, and the ensuing excellent on sky results, including the detection of the three exoplanets orbiting the star HR8799.

mgs↗

Evaluating the Performance of Unmanned Ground Vehicle Water Detection

Water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation over cross-country terrain. During the Robotics Collaborative Technology Alliances (RCTA) program, the Jet Propulsion Laboratory (JPL) developed a set of water detection algorithms that are used to detect, localize, and avoid water bodies large enough to be a hazard to a UGV. The JPL water detection software performs the detection and localization stages using a forward-looking stereo pair of color cameras. The 3D coordinates of water body surface points are then output to a UGV's autonomous mobility system, which is responsible for planning and executing safe paths. There are three primary methods for evaluating the performance of the water detection software. Evaluations can be performed in image space on the intermediate detection product, in map space on the final localized product, or during autonomous navigation to characterize the avoidance of a variety of water bodies. This paper describes a methodology for performing the first two types of water detection performance evaluations.

stereo vision↗

The Quest for an OCO (Orbiting Carbon Observatory) Re-Flight

The objective of the OCO (Orbiting Carbon Observatory) mission was to make the first space-based measurements of atmospheric carbon dioxide with the accuracy needed to quantify sources and sinks of this important greenhouse gas. Unfortunately, the observatory was lost as a result of a launch vehicle failure on 24 February 2009. The JPL (Jet Propulsion Laboratory) was directed to assess the options for the re-flight of the OCO instrument and recovery of the carbon-related measurement, and to understand and quantitatively assess the cost, schedule, and technical and programmatic risks of the identified options. The two most likely solutions were (1) a shared platform with the TIRS (Thermal Infrared Sensor) instrument and (2) a dedicated OSC (Orbital Sciences Corporation) LEOStar-2 spacecraft bus similar to that utilized for the original OCO mission. A joint OCO-TIRS mission study was commissioned and two specific options were examined. However, each presented technical challenges that would drive cost. It was determined that the best option was to rebuild the OCO observatory to the extent possible including another LEOStar-2 spacecraft bus. This lowest risk approach leverages the original OCO design and provides the shortest path to launch, which is targeted for no later than the February 2013 timeframe.

carbon↗

Design and Development of the MSL Descent Stage Propulsion System

On August 5, 2012, The Mars Science Laboratory mission successfully landed the largest interplanetary rover ever built, Curiosity, on the surface of Mars. The Entry, Descent, and Landing (EDL) phase of this mission was by far the most complex landing ever attempted on a planetary body. The Descent Stage Propulsion System played an integral and critical role during Curiosity's EDL. The Descent Stage Propulsion System was a one of a kind hydrazine propulsion system designed specifically for the EDL phase of the MSL mission. It was designed, built, and tested at the Jet Propulsion Laboratory (JPL). The purpose of this paper is to present an overview of the design and development of the MSL Descent Stage Propulsion System. Driving requirements, system design, component selection, operational sequence of the system at Mars, new developments, and key challenges will be discussed.

Weiss, Jeffrey M.↗

Technologies for Low Frequency Radio Observations of the Cosmic Dawn

The Jet Propulsion Laboratory (JPL) is developing concepts and technologies for low frequency radio astronomy space missions aimed at observing highly redshifted neutral Hydrogen from the Dark Ages. This is the period of cosmic history between the recombination epoch when the microwave background radiation was produced and the re-ionization of the intergalactic medium by the first generation of stars (Cosmic Dawn). This period, at redshifts greater than about 20, is a critical epoch for the formation and evolution of large-scale structure in the universe. The 21-cm spectral line of Hydrogen provides the most promising method for directly studying the Dark Ages, but the corresponding frequencies at such large redshifts are only tens of MHz and thus require space-based observations to avoid terrestrial RFI and ionospheric absorption and refraction. This paper reports on the status of several low frequency technology development activities at JPL, including deployable bi-conical dipoles for a planned lunar-orbiting mission, and both rover-deployed and inflation-deployed long dipole antennas for use on the lunar surface.

Cosmic Dark Ages↗

Science Benefits of Onboard Spacecraft Navigation

Primitive bodies (asteroids and comets), which have remained relatively unaltered since their formation, are important targets for scientific missions that seek to understand the evolution of the solar system. Often the first step is to fly by these bodies with robotic spacecraft. The key to maximizing data returns from these flybys is to determine the spacecraft trajectory relative to the target body-in short, navigate the spacecraft- with sufficient accuracy so that the target is guaranteed to be in the instruments' field of view. The most powerful navigation data in these scenarios are images taken by the spacecraft of the target against a known star field (onboard astrometry). Traditionally, the relative trajectory of the spacecraft must be estimated hours to days in advance using images collected by the spacecraft. This is because of (1)!the long round-trip light times between the spacecraft and the Earth and (2)!the time needed to downlink and process navigation data on the ground, make decisions based on the result, and build and uplink instrument pointing sequences from the results. The light time and processing time compromise navigation accuracy considerably, because there is not enough time to use more accurate data collected closer to the target-such data are more accurate because the angular capability of the onboard astrometry is essentially constant as the distance to the target decreases, resulting in better "plane-of- sky" knowledge of the target. Excellent examples of these timing limitations are high-speed comet encounters. Comets are difficult to observe up close; their orbits often limit scientists to brief, rapid flybys, and their coma further restricts viewers from seeing the nucleus in any detail, unless they can view the nucleus at close range. Comet nuclei details are typically discernable for much shorter durations than the roundtrip light time to Earth, so robotic spacecraft must be able to perform onboard navigation. This onboard navigation can be accomplished through a self- contained system that by eliminating light time restrictions dramatically improves the relative trajectory knowledge and control and subsequently increases the amount of quality data collected. Flybys are one-time events, so the system's underlying algorithms and software must be extremely robust. The autonomous software must also be able to cope with the unknown size, shape, and orientation of the previously unseen comet nucleus. Furthermore, algorithms must be reliable in the presence of imperfections and/or damage to onboard cameras accrued after many years of deep-space operations. The AutoNav operational flight software packages, developed by scientists at the Jet Propulsion Laboratory (JPL) under contract with NASA, meet all these requirements. They have been directly responsible for the successful encounters on all of NASA's close-up comet-imaging missions (see Figure !1). AutoNav is the only system to date that has autonomously tracked comet nuclei during encounters and performed autonomous interplanetary navigation. AutoNav has enabled five cometary flyby missions (Table!1) residing on four NASA spacecraft provided by three different spacecraft builders. Using this software, missions were able to process a combined total of nearly 1000 images previously unseen by humans. By eliminating the need to navigate spacecraft from Earth, the accuracy gained by AutoNav during flybys compared to ground-based navigation is about 1!order of magnitude in targeting and 2!orders of magnitude in time of flight. These benefits ensure that pointing errors do not compromise data gathered during flybys. In addition, these benefits can be applied to flybys of other solar system objects, flybys at much slower relative velocities, mosaic imaging campaigns, and other proximity activities (e.g., orbiting, hovering, and descent/ascent).

Autonomy↗