Cynthia Y. Cheung

Tetrahedral Robotics for Space Exploration

A reconfigurable space filling robotic architecture has a wide range of possible applications. One of the more intriguing possibilities is mobility in very irregular and otherwise impassable terrain. NASA Goddard Space Flight Center is developing the third generation of its addressable reconfigurable technology (ART) tetrahedral robotics architecture. An ART-based variable geometry truss consisting of 12 tetrahedral elements made from 26 smart struts on a wireless network has been developed. The primary goal of this development is the demonstration of a new kind of robotic mobility that can provide access and articulation that complement existing capabilities. An initial set of gaits and other behaviors are being tested, and accommodations for payloads such as sensor and telemetry packages are being studied. Herein, we describe our experience with the ART tetrahedral robotics architecture and the improvements implemented in the third generation of this technology. Applications of these robots to space exploration and the tradeoffs involved with this architecture will be discussed.

Neural Basis Function Control of Super Micro Autonomous Reconfigurable Technology (SMART) Nano-Systems

** Nanotechnology, taken to its full three-dimensional potential, will place within the volume of a cube of sugar systems of vast complexity that far exceed the quantitative and qualitative capabilities of today’s largest supercomputers. Currently, the uncertainty and imprecision of the real world is tamed, rigidly fixed, by addressable, digital techniques and the careful orchestration of digital patterns within our machines. How to handle the interaction between our digitally implemented systems and continuous, disorganized nature is a key question. NASA is currently researching ways to move beyond autonomy implemented as bruteforce control over every degree of freedom we can discover in our systems. Our systems operate in natural environments: inhumanly harsh, unfamiliar, unknown, and uncontrolled environments. Nature often surprises us, and so we turn to natural systems for clues about how to make massively complex systems more robust, reliable, and truly autonomous. Turning to Computer Science we draw on what we’ve learned about multi-agent systems running continuously and autonomously to understand information flow at the highest semantic levels. From physics we recall that the behaviors of systems may often be enumerated in a basis of fundamental behaviors. Non-linear physics contains clues about how to connect the physical world with the patterns of electric signals that make up the soft, information component of the systems. Genetics and control theory instruct how to handle long and short-term feedbacks throughout the system. Chemistry and biology provide important guiding principles governing system functions.

SPARCLE: Electrostatic Tool for Lunar Dust Control

Successful exploration of most planetary surfaces, with their impact‐generated dusty regoliths, will depend on the capabilities to keep surfaces free of the dust which could compromise performance and to collect dust for characterization. Solving the dust problem is essential before we return to the Moon. During the Apollo missions, the discovery was made that regolith fines, or dust, behaved like abrasive velcro, coating surfaces, clogging mechanisms, and making movement progressively more difficult as it was mechanically stirred up during surface operations, and abrading surfaces, including spacesuits, when attempts were made to remove it manually. In addition, some of the astronauts experienced breathing difficulties when exposed to dust that got into the crew compartment. The successful strategy will deal with dust dynamics resulting from interaction between mechanical and electrostatic forces. Here we will describe the surface properties of dust particles, the basis for their behavior, and an electro...

Mobile science platforms for impassable terrain

Some of the most scientifically interesting terrain is among the most inaccessible, presenting problems for all mobility strategies. Lava flows, for example, can have structure at all scale sizes rendering traversal via appendage or wheel difficult at best. NASA researchers have been developing an innovative mechanical structure that provides mobility in terrain unnavigable by wheeled or even legged vehicles. We are developing a mobile science platform (MSP) that is completely symmetric, with neither top nor bottom, so that it cannot fall down and fail to get up. The MSP actively navigates its environment to place its payload or gathers samples in places otherwise unreachable, e.g., the lunar highlands or rugged volcanic terrains on Mars

Evolving a self -organizing neuromechanical system for self -healing aerospace structures

§NASA is developing a novel articulated truss built from a highly redundant, highly integrated network of actuators. Near -term implementations of this truss a rchitecture make use of Addressable Reconfigurable Technology (ART) and can be centrally controlled as, for example, one’s hand is directed by the central nervous system. Mid -to -far term implementations make increasing use of micro - and nano -technologies to allow truss systems to scale eventually through thousands of nodes and beyond into the realm of Super Miniaturized Addressable Reconfigurable Technology (SMART). Structures made from this material may take on shapes as required to meet mission requirem ents for deployment, storage, locomotion, shape control, and so on. One of the key applications of this technology is for nano - and pico -spacecraft. Furthermore, the large number of redundant elements opens up many possibilities to address and mitigate fa ults and failures within the truss. Not only does this architecture provide physical reconfiguration, system control must be able to adapt to its new configuration. In this work, we describe a new control architecture for a synthetic neural system design ed to meet this challenge. Genetic algorithmic evolution within supercomputer -based simulations allows the system components to situate themselves amongst each other and their environment. The synthetic neural system is based on composable behavioral uni ts called Neural Basis Functions (NBF) that provide a way to unify low -level autonomic and high -level reasoning in a single operational architecture. Distributed systems fit naturally within this framework. We describe fault modes of and recoveries enable d by the architecture and the results of our first attempts to construct a synthetic neural system based on NBFs with a focus on the self -organizing and self -healing properties of the system. We emphasize the scaling issues associated with the large number of nodes in nano -technology -based SMART structures and how distributed systems, e.g. multi -spacecraft systems, are controlled.

Thriving in the irregular and the unknown: system control for space exploration

Crucial to the development of a system of systems infrastructure for space exploration is a truly scalable control architecture. This architecture must be built on the reliable, adaptable operation and co-operation of autonomous systems at multiple levels. Advances in hardware and software computing technology allow us to consider anew the range of control systems from reactive, lowlevel to deliberate, heuristic systems. At NASA’s Goddard Space Flight Center (GSFC), we have been developing the means to create space and surface systems that are active participants in their environment rather than being merely visitors that withstand space’s hazards as our extended remotely controlled tools. Central to this work has been the development of the Autonomous Nano-Technology Swarm (ANTS) mission architecture and the Neural Basis Function Synthetic Neural System (NBF/SNS) which are included among the subjects of several GSFC provisional patent applications. These are scalable systems with non-linear dynamics built in to deal with irregularity, uncertainty, and unpredictability in their environments. These system architectures outline pathways from existing near-term capabilities to far-term enabling technologies.

New Frontiers in NASA Data Management

We discuss NASA’s data management practices, showing how they are rooted in policies established early during the space science era. We describe current trends and future directions in NASA data management. Data preservation has always been a high priority. New information technologies have enabled faster and more convenient data access, including access to NASA’s holdings by students, educators, and the general public. Multiwavelength data analyses are now common, and it will soon become possible to mine information from a “virtual observatory” comprised of terabyte-size digital sky surveys that span the entire electromagnetic spectrum. We give examples of some of the current and next-generation tools that will make this possible.

THE CENTRAL ROLE OF RECONNECTION IN SPACE PLASMA PHENOMENA TARGETED BY THE MAGNETOSPHERIC MULTISCALE MISSION

Abstract The Magnetospheric Multiscale Mission, which consists of four identically instrumented spacecraft flying in close formation, will allow the first extensive characterization of the 3D structure and dynamic variations of the magnetosphere on scales down to electron inertial length. By targeting the magnetopause and magnetotail, two regions already known to provide observations crucial to understanding the reconnection process, the mission will determine the spatial and temporal scales of basic plasma processes.

An archival survey of the HDF-South

We present the results of a survey of archival data and catalogued objects in the region around the Southern Hubble Deep Field (HDF-South). The survey encompasses NASA mission logs, astronomical catalogs, and journal tables. The HDF-South (HDF-S) has been the focus of a dedicated HST observing campaign during October 1998. Many astrophysically interesting objects in the vicinity of the HDF-S, including quasars and clusters of galaxies, have been catalogued and observed at a wide range of wavelengths. The byproducts of this and similar user-selected surveys of archival data can be used to study classes of objects that may potentially be represented among the faint objects discovered within the HDF-S. This survey was conducted using a suite of new data search, browse, and visualization tools available at the NASA ADC (Astronomical Data Center: http://adc.gafc.nasa.gov/).