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NASA NTRS2018

Towards Explainability of UAV-Based Convolutional Neural Networks for Object Classification

f autonomous systems using trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR), a new NASA Convergent Aeronautical Solutions (CAS) Project. One critical research element of ATTRACTOR is explainability of the decision-making across relevant subsystems of an autonomous system. The ability to explain why an autonomous system makes a decision is needed to establish a basis of trustworthiness to safely complete a mission. Convolutional Neural Networks (CNNs) are popular visual object classifiers that have achieved high levels of classification performances without clear insight into the mechanisms of the internal layers and features. To explore the explainability of the internal components of CNNs, we reviewed three feature visualization methods in a layer-by-layer approach using aviation related images as inputs. Our approach to this is to analyze the key components of a classification event in order to generate component labels for features of the classified image at different layers of depths. For example, an airplane has wings, engines, and landing gear. These could possibly be identified somewhere in the hidden layers from the classification and these descriptive labels could be provided to a human or machine teammate while conducting a shared mission and to engender trust. Each descriptive feature may also be decomposed to a combination of primitives such as shapes and lines. We expect that knowing the combination of shapes and parts that create a classification will enable trust in the system and insight into creating better structures for the CNN.

Dolph, Chester V.↗
NASA NTRS1985

The Space Flight Operations Center development project

This paper presents an overview of the Jet Propulsion Laboratory's (JPL) plan for developing a multi-mission facility called the Space Flight Operations Center (SFOC). The SFOC development is a five-year project with the objective of developing and adapting up-to-date computing, networking and data management technology to meet the future data processing and data management requirements for JPL's flight project mission operations. Presented are the project background, basic goals and objectives, design concept and project implementation approach.

Ebersole, M. M.↗
NASA NTRSDate not supplied

An Optimization Approach to Support Science Decision Making for Lunar Surface Exploration

Introduction: Scientific exploration is one of the three pillars of NASA’s Moon2Mars architecture, with crew surface extra vehicular activities (EVA) serving a critical enabling function. Development of surface EVA operational planning and execution, specifically integrating science and flight control teams (FCT), is currently being explored through analog scenarios. This integration, exercised, for example, through the Joint EVA and Hu-man Surface Mobility Test Team (JETT), allows for science input on EVA activities in near real-time through a Science Evaluation Room (SER), or Arte-mis science backroom, which integrates with the broader FCT through the Science Officer. The SER works within the FCT to support dynamic EVA planning in response to changes in operational constraints as well as science opportunities and re-prioritization, increasing the mission science return and accelerating the accomplishment of the Moon2Mars science objectives. The SER works within the FCT to provide recommendations to traverse execution in near real-time. One challenge is the requirement to deliver SER inputs to the FCT on operationally relevant timelines. Failure to do so may result in suboptimal execution of science exploration EVAs or even loss of key science objectives. To close this gap, we present a network optimization tool to allow the SER to provide rapid input to the FCT in response to changes in operational constraints or science opportunities. Inputs are predicated on approved science objectives, and clear rationale must be provided to the FCT for any requested change. Accordingly, this tool incorporates the Science Traceability Matrix (STM), SER prioritization scheme, and station characterization and action planning with operational constraints such as duration, traverse speed, and distance to maximize science objectives based on SER priorities, consistent with FCT operational requirements. Method: As a proof of concept, we used an existing linear programing software package used to simulate optimal routes through cellular metabolism. We built a Demonstrative Model with three STM objectives and four stations on a region of the Moon. The objectives were given an arbitrary prioritization and mapped to the stations through four possible crew actions. (Figs. 1 and 2). This station to STM mapping is consistent with the method used by the JETT5 Science Team to develop analog surface EVA science planning. We used a grid system with the landing site at the origin and the four stations placed across the positive x,y quadrant. Actions were assigned to each station and the accomplishment of those actions resulted in a numerical “reward” based on the ability of that action to achieve science objectives. The aggregate reward from each individual STM objective contributes to a global score (Science Yield), weighted by its priority. Operational constraints included a requirement to start and end at the landing site, 5 minutes each for initial station characterization and “clean up,” and variable total EVA time, traverse rate (fixed to 0.5 meters per second in our example), and time to perform each action (10, 5, 7, and 15 min for actions 1, 2, 3, and 4, respectively). Additional constraints and variables will be added in the future (e.g., sample mass, number of stations, traverse route constraints, illumination). Optimization. We converted the connections (arcs) between these stations (nodes) into a mixed integer linear programming optimization problem (arcs = constraints, nodes = variables) with the objective to maximize Science Yield. For any action, the Science Yield is equal to the relevance of that action to an STM objective [3, 2, and 1 point(s) for High, Med., and Low relevance, respectively], multiplied by the STM Objective Priority [3, 2, and 1 point(s) for High, Med., and Low priority, respectively]. This resulted in a model that computes the optimal station and action combination to maximize the Science Yield. These weightings can be adjusted by the SER as desired. Results: We explored three test cases for the Demonstrative Model. First, we set the maximum EVA duration to 120 minutes and computed the optimal route (Fig. 3A). The model suggested per-forming Actions 1 and 2 at Station P01, followed by Actions 1 and 2 at Station P02, and finally Actions 1 and 3 at Station P04 before returning to the Landing Site. Second, we adjusted the STM Objective Priori-ty order and computed the new optimal route (Fig. 3B). Under this situation, the model suggested per-forming all Actions at Station P02 followed by all Actions at Station P03. The previous test cases were relevant to SER planning activities. Next, we explored providing mid-EVA replanning input to the FCT. Scenario: While executing the Route in Fig. 3A the crew finishes at Station P01 and FCT decides that the EVA needs to finish in 45 minutes back at the Landing Site. FCT asks SER to recommend changes to the plan to accommodate this operation-al change. Using the model and incorporating these new constraints (start at Station P01, max. time of 45 min), the model suggested performing Actions 2 and 4 at Station P03 (Fig. 4), requiring 41 minutes to complete and return to the Landing Site. Interestingly, Station 3 was not part of the original route. Using the model, we determined the EVA would need 66 minutes, instead of 45, in order for the original Station P04 to yield a larger Science Yield than Station P03. The parametrization and simulation was per-formed in less than a minute, demonstrating the operational relevance of the approach. Future Efforts: The results from the Demonstrative Model suggest this tool can accelerate SER decision making on operationally relevant timelines. Use in analog activities, such as JETT5 or follow-ons, which have over a dozen stations for a crew to explore and over a dozen actions per station, will provide needed validation of the utility of this tool for planning EVAs, replanning mid-EVA, or planning follow-on EVAs based on previous results. Further integration with FCT execution monitoring tools may provide additional efficiency gains, al-lowing rapid and iterative exploration of operation-al and science decision space by the FCT and SER.

Science Operations↗
NASA NTRS1989

The structure of the clouds distributed operating system

A novel system architecture, based on the object model, is the central structuring concept used in the Clouds distributed operating system. This architecture makes Clouds attractive over a wide class of machines and environments. Clouds is a native operating system, designed and implemented at Georgia Tech. and runs on a set of generated purpose computers connected via a local area network. The system architecture of Clouds is composed of a system-wide global set of persistent (long-lived) virtual address spaces, called objects that contain persistent data and code. The object concept is implemented at the operating system level, thus presenting a single level storage view to the user. Lightweight treads carry computational activity through the code stored in the objects. The persistent objects and threads gives rise to a programming environment composed of shared permanent memory, dispensing with the need for hardware-derived concepts such as the file systems and message systems. Though the hardware may be distributed and may have disks and networks, the Clouds provides the applications with a logically centralized system, based on a shared, structured, single level store. The current design of Clouds uses a minimalist philosophy with respect to both the kernel and the operating system. That is, the kernel and the operating system support a bare minimum of functionality. Clouds also adheres to the concept of separation of policy and mechanism. Most low-level operating system services are implemented above the kernel and most high level services are implemented at the user level. From the measured performance of using the kernel mechanisms, we are able to demonstrate that efficient implementations are feasible for the object model on commercially available hardware. Clouds provides a rich environment for conducting research in distributed systems. Some of the topics addressed in this paper include distributed programming environments, consistency of persistent data and fault-tolerance.

Dasgupta, Partha↗
NASA NTRS1993

Object-oriented Tools for Distributed Computing

Distributed computing systems are proliferating, owing to the availability of powerful, affordable microcomputers and inexpensive communication networks. A critical problem in developing such systems is getting application programs to interact with one another across a computer network. Remote interprogram connectivity is particularly challenging across heterogeneous environments, where applications run on different kinds of computers and operating systems. NetWorks! (trademark) is an innovative software product that provides an object-oriented messaging solution to these problems. This paper describes the design and functionality of NetWorks! and illustrates how it is being used to build complex distributed applications for NASA and in the commercial sector.

Adler, Richard M.↗
NASA NTRS1989

Design issues in 2-port network models of bilateral remote manipulation

A two-port impedance-network model of a single-degree-of-freedom remote manipulation system in which a human operator at the master port interacts with a task object at the slave port in a remote location is presented. The design of the network involves the selection of feedback gains for the servomechanisms that transmit motion and force information from one port of the two-port to the other in both directions. The proposed methodology allows this selection to be based on both stability requirements and specifications of desired port impedances, given models of the task and the human operator. The resulting design guidelines guarantee stability for any passive task object at the slave port and any passive human impedance at the master port.

Raju, G. Jagannath↗
NASA NTRS1993

Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator.

Decker, Arthur J.↗
NASA NTRS2011

Engineering and Technology Challenges for Active Debris Removal

After more than fifty years of space activities, the near-Earth environment is polluted with man-made orbital debris. The collision between Cosmos 2251 and the operational Iridium 33 in 2009 signaled a potential collision cascade effect, also known as the "Kessler Syndrome", in the environment. Various modelling studies have suggested that the commonly-adopted mitigation measures will not be sufficient to stabilize the future debris population. Active debris removal must be considered to remediate the environment. This paper summarizes the key issues associated with debris removal and describes the technology and engineering challenges to move forward. Fifty-four years after the launch of Sputnik 1, satellites have become an integral part of human society. Unfortunately, the ongoing space activities have left behind an undesirable byproduct orbital debris. This environment problem is threatening the current and future space activities. On average, two Shuttle window panels are replaced after every mission due to damage by micrometeoroid or orbital debris impacts. More than 100 collision avoidance maneuvers were conducted by satellite operators in 2010 to reduce the impact risks of their satellites with respect to objects in the U.S. Space Surveillance Network (SSN) catalog. Of the four known accident collisions between objects in the SSN catalog, the last one, collision between Cosmos 2251 and the operational Iridium 33 in 2009, was the most significant. It was the first ever accidental catastrophic destruction of an operational satellite by another satellite. It also signaled the potential collision cascade effect in the environment, commonly known as the "Kessler Syndrome," predicted by Kessler and Cour-Palais in 1978 [1]. Figure 1 shows the historical increase of objects in the SSN catalog. The majority of the catalog objects are 10 cm and larger. As of April 2011, the total objects tracked by the SSN sensors were more than 22,000. However, approximately 6000 of them had yet to be fully processed and entered into the catalog. This population had been dominated by fragmentation debris throughout history. Before the anti-satellite test (ASAT) conducted by China in 2007, the fragmentation debris were almost all explosion fragments. After the ASAT test and the collision between Iridium 33 and Cosmos 2251, the ratio of collision fragments to explosion fragments was about one-to-one. It is expected that accidental collision fragments will further dominate the environment in the future.

Liou, Jer-Chyi↗
NASA NTRS1990

Application of inertial instruments for DSN antenna pointing and tracking

The feasibility of using inertial instruments to determine the pointing attitude of the NASA Deep Space Network antennas is examined. The objective is to obtain 1 mdeg pointing knowledge in both blind pointing and tracking modes to facilitate operation of the Deep Space Network 70 m antennas at 32 GHz. A measurement system employing accelerometers, an inclinometer, and optical gyroscopes is proposed. The initial pointing attitude is established by determining the direction of the local gravity vector using the accelerometers and the inclinometer, and the Earth's spin axis using the gyroscopes. Pointing during long-term tracking is maintained by integrating the gyroscope rates and augmenting these measurements with knowledge of the local gravity vector. A minimum-variance estimator is used to combine measurements to obtain the antenna pointing attitude. A key feature of the algorithm is its ability to recalibrate accelerometer parameters during operation. A survey of available inertial instrument technologies is also given.

Eldred, D. B.↗
NASA NTRS1992

Neural network training by integration of adjoint systems of equations forward in time

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically, it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved, but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. The trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

Toomarian, Nikzad↗
NASA NTRS1999

Neural Network Training by Integration of Adjoint Systems of Equations Forward in Time

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically. it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved. but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. Tbc trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

Toomarian, Nikzad↗
NASA NTRS2003

Recent results in Mars Relay Network planning and scheduing

At different time periods in the future, Mars missions will overlap and previous studies indicate that during such periods existing deep space communication infrastructure will not be able to handle all Mars communication needs. A plausible solution is to perform optimal resource allocation for the Mars relay communication network; a network consisting of multiple surface units and orbiters on Mars and the Deep Space Stations. Unlike direct-to-earth, a relay communication, either in real-time or store-and-forward, can increase network science data return, reduce surface unit's direct-to-earth communication demands, and enable communication even when the surface unit is not facing Earth. It is the objective of this paper to take advantage of the relay operation to efficiently plan and schedule the network communications.

Relay Network planning and scheduling constrained ↗
NASA NTRS1993

Mobile and replicated alignment of arrays in data-parallel programs

When a data-parallel language like FORTRAN 90 is compiled for a distributed-memory machine, aggregate data objects (such as arrays) are distributed across the processor memories. The mapping determines the amount of residual communication needed to bring operands of parallel operations into alignment with each other. A common approach is to break the mapping into two stages: first, an alignment that maps all the objects to an abstract template, and then a distribution that maps the template to the processors. We solve two facets of the problem of finding alignments that reduce residual communication: we determine alignments that vary in loops, and objects that should have replicated alignments. We show that loop-dependent mobile alignment is sometimes necessary for optimum performance, and we provide algorithms with which a compiler can determine good mobile alignments for objects within do loops. We also identify situations in which replicated alignment is either required by the program itself (via spread operations) or can be used to improve performance. We propose an algorithm based on network flow that determines which objects to replicate so as to minimize the total amount of broadcast communication in replication. This work on mobile and replicated alignment extends our earlier work on determining static alignment.

Chatterjee, Siddhartha↗
NASA NTRS2000

The Network Configuration of an Object Relational Database Management System

The networking and implementation of the Oracle Database Management System (ODBMS) requires developers to have knowledge of the UNIX operating system as well as all the features of the Oracle Server. The server is an object relational database management system (DBMS). By using distributed processing, processes are split up between the database server and client application programs. The DBMS handles all the responsibilities of the server. The workstations running the database application concentrate on the interpretation and display of data.

Diaz, Philip↗
NASA NTRS2016

A Benefit Analysis of Infusing Wireless into Aircraft and Fleet Operations - Report to Seedling Project Efficient Reconfigurable Cockpit Design and Fleet Operations Using Software Intensive, Network Enabled, Wireless Architecture (ECON)

We report on an examination of potential benefits of infusing wireless technologies into various areas of aircraft and airspace operations. The analysis is done in support of a NASA seedling project Efficient Reconfigurable Cockpit Design and Fleet Operations Using Software Intensive, Network Enabled Wireless Architecture (ECON). The study has two objectives. First, we investigate one of the main benefit hypotheses of the ECON proposal: that the replacement of wired technologies with wireless would lead to significant weight reductions on an aircraft, among other benefits. Second, we advance a list of wireless technology applications and discuss their system benefits. With regard to the primary hypothesis, we conclude that the promise of weight reduction is premature. Specificity of the system domain and aircraft, criticality of components, reliability of wireless technologies, the weight of replacement or augmentation equipment, and the cost of infusion must all be taken into account among other considerations, to produce a reliable estimate of weight savings or increase.

Alexandrov, Natalia↗
NASA NTRS2015

Converter Compressor Building, SWMU 089, Hot Spot Areas 1, 2, and 5 Operations, Maintenance, and Monitoring Report, Kennedy Space Center, Florida

This Operations, Maintenance, and Monitoring Report (OMMR) presents the findings, observations, and results from operation of the air sparging (AS) interim measure (IM) for Hot Spot (HS) Areas 1, 2, and 5 at the Converter Compressor Building (CCB) located at Kennedy Space Center (KSC), Florida. The objective of the IM at CCB HS Areas 1, 2, and 5 is to decrease concentrations of volatile organic compounds (VOCs) in groundwater in the treatment zones via AS to levels that will enable a transition to a monitored natural attenuation (MNA) phase. This OMMR presents system operations and maintenance (O&M) information and performance monitoring results since full-scale O&M began in June 2014 (2 months after initial system startup in April 2014), including quarterly performance monitoring events in July and October 2014 and January and May 2015. Based on the results to date, the AS system is operating as designed and is meeting the performance criteria and IM objective. The performance monitoring network is adequately constructed for assessment of IM performance at CCB HS Areas 1, 2, and 5. At the March 2014 KSC Remediation Team (KSCRT) Meeting, team consensus was reached for the design prepared for expansion of the system to treat the HS 4 area, and at the November 2014 KSCRT Meeting, team consensus was reached that HS 3 was adequately delineated horizontally and vertically and for selection of AS for the remedial approach for HS 3. At the July 2015 KSCRT meeting, team consensus was reached to continue IM operations in all zones until HSs 3 and 4 is operational, once HS 3 and 4 zones are operational discontinue operations in HS 1, 2, and 5 zones where concentrations are less than GCTLs to observe whether rebounding conditions occur. Team consensus was also reached to continue quarterly performance monitoring to determine whether operational zones achieve GCTLs and to continue annual IGWM of CCB-MW0012, CCBMW0013, and CCB-MW0056, located south of the treatment area. The next performance monitoring event is scheduled for July 2015.

Converter Compressor Building↗
NASA NTRS1989

A class Hierarchical, object-oriented approach to virtual memory management

The Choices family of operating systems exploits class hierarchies and object-oriented programming to facilitate the construction of customized operating systems for shared memory and networked multiprocessors. The software is being used in the Tapestry laboratory to study the performance of algorithms, mechanisms, and policies for parallel systems. Described here are the architectural design and class hierarchy of the Choices virtual memory management system. The software and hardware mechanisms and policies of a virtual memory system implement a memory hierarchy that exploits the trade-off between response times and storage capacities. In Choices, the notion of a memory hierarchy is captured by abstract classes. Concrete subclasses of those abstractions implement a virtual address space, segmentation, paging, physical memory management, secondary storage, and remote (that is, networked) storage. Captured in the notion of a memory hierarchy are classes that represent memory objects. These classes provide a storage mechanism that contains encapsulated data and have methods to read or write the memory object. Each of these classes provides specializations to represent the memory hierarchy.

Russo, Vincent F.↗
NASA NTRS2004

Overview of GPM Missions's Ground Validation Program

An important element of the internationally structured Global Precipitation Measurement (GPM) mission will be its ground validation research program. Within the last year, the initial architecture of this program has taken shape. This talk will describe that architecture, both in terms of the international program and in terms of the separate regional programs of the principle participating space agencies, i.e., ESA, JAXA, and NASA. There are three overriding goals being addressed in the planning of this program; (1) establishing various new, challenging and important scientific research goals vis-a-vis current ground validation programs supporting satellite retrieval of precipitation; (2) designing the program as an international partnership which operates, out of necessity, heterogeneous sites in terms of their respective observational foci and science thrusts, but anneals itself in terms of achieving a few overarching scientific objectives; and (3) developing a well-designed protocol that allows specific sites or site networks, at their choosing, to operate in a 'supersite' mode - defined as the capability to routinely transmit GV information at low latency to GPM's Precipitation Processing System (PPS). (The PPS is being designed as GPM's data information system, a distributed data system with main centers at the Goddard Space Flight Center (GSFC) within NASA, the Earth Observation Research Center (EORC) within JAXA, and a TBD facility to be identified by the ESA s ESTEC facility in Noordwijk.)

Smith, Eric A.↗