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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Autonomous Assembly of Modular Structures in Space and on Extraterrestrial Locations

The fulfillment of the new US. National Vision for Space Exploration requires many new enabling technologies to accomplish the goal of utilizing space for commercial activities and for returning humans to the moon and extraterrestrial environments. Traditionally, flight structures are manufactured as complete systems and require humans to complete the integration and assembly in orbit. These structures are bulky and require the use of heavy launch vehicles to send the units to the desired location, e.g. International Space Station (ISS). This method requires a high degree of safety, numerous space walks and significant cost for the humans to perform the assembly in orbit. For example, for assembly and maintenance of the ISS, 52 Extravehicular Activities (EVA's) have been performed so far with a total EVA time of approximately 322 hours. Sixteen (16) shuttle flights haw been to the ISS to perform these activities with an approximate cost of $450M per mission. For future space missions, costs have to be reduced to reasonably achieve the exploration goals. One concept that has been proposed is the autonomous assembly of space structures. This concept is an affordable, reliable solution to in-space and extraterrestrial assembly operations. Assembly is autonomously performed when two components containing onboard electronics join after recognizing that the joint is appropriate and in the precise position and orientation required for assembly. The mechanism only activates when the specifications are correct and m a nominal range. After assembly, local sensors and electronics monitor the integrity of the joint for feedback to a master controller. To achieve this concept will require a shift in the methods for designing space structures. In addition, innovative techniques will be required to perform the assembly autonomously. Monitoring of the assembled joint will be necessary for safety and structural integrity. If a very large structure is to be assembled in orbit, then the number of integrity sensors will be significant. Thus simple, low cost sensors are integral to the success of this concept. This paper will address these issues and will propose a novel concept for assembling space structures autonomously. The paper will present Several autonomous assembly methods. Core technologies required to achieve in space assembly will be discussed and novel techniques for communicating, sensing, docking and assembly will be detailed. These core technologies are critical to the goal of utilizing space in a cost efficient and safe manner. Finally, these technologies can also be applied to other systems both on earth and extraterrestrial environments.

Alhorn, Dean C.↗
NASA NTRS1989

Mars Rover and Sample Return Mission design

The current reference Mars Rover and Sample Return mission is described. Technical issues are outlined, including high-resolution image acquisition and reconstruction, approach navigation, ground and flight systems operational complexity, rover autonomy, autonomous rendezvous and docking in Mars orbit, aerocapture and aeromaneuver, estimating the probability of mission success, and end-to-end information system design. Focus is placed on lander hazard identification and avoidance, pinpoint landing guidance and control, Mars ascent vehicle guidance and control, planetary protection and quarantine, sample acquisition and preservation, project management and control, systems requirements and interface control, and costing. In addition, program issues such as international participation, fiscal constraints, and launch-vehicle availability are considered.

Kwok, Johnny H.↗
NASA NTRSDate not supplied

Microbial Optical Data Processing: A Key Step in the Metabolic Assessment of Lunar Explorer Instrument for Space Biology Applications (LEIA) and Biosentinel’s Payload Data

The BioSensor payload platform on BioSentinel and LEIA autonomously collects optical data from microbial model organisms in liquid culture. The BioSensor is designed to monitor metabolic activity using absorbance measurements of cell density and alamarBlue, a readily available colorimetric redox indicator dye. BioSentinel, a pioneering NASA CubeSat, uses yeast to study deep space radiation. LEIA investigates radiation and lunar gravity response. The experimental setup includes 16 wells equipped with three LEDs (570, 630, and 850 nm) and their corresponding photodetectors. One well is a calibration control without biology while the rest have desiccated cultures. Autonomous rehydration initiates the experiment. Data from the BioSensor are received from the flight and ground units, enabling comparison to uncover location-based metabolic rate variations. This study presents a Python Jupyter notebook developed for efficient data processing of multiple CSV files containing date and time columns, temperature, and well illumination data. It offers a user-friendly interface while maintaining computational power, automatically recognizing and iteratively processing data files in a user-input path. A Hampel filter with a short window eliminates outlier artifacts from sensor dropout. Because absorbance is a relative measurement, conversion from raw illumination requires defining a “blank” value, so the first data points are averaged to provide the necessary denominator. A cube-root function correction mitigates undesired drift caused by air pockets during the fluidic card filling phase, maintaining optical path length consistency. Beer-Lambert's law is applied to further convert absorbance values to cell and dye form concentrations, the desired science parameters. The processed data are saved and visualized as SVG plots. Future plans include extracting specific science parameters from the processed data like growth rate and metabolic rate, and identification of features corresponding to metabolic and phenotypic shifts such as starvation, shifts from aerobic to anaerobic growth, and osmotic stresses.

Space biology↗
NASA NTRS2011

A Multifunctional Coating for Autonomous Corrosion Control

Nearly all metals and their alloys are subject to corrosion that causes them to lose their structural integrity or other critical functionality. Protective coatings are the most commonly used method of corrosion control. However, progressively stricter environmental regulations have resulted in the ban of many commercially available corrosion protective coatings due to the harmful effects of their solvents or corrosion inhibitors. This work concerns the development of a multifunctional smart coating for the autonomous control of corrosion. This coating is being developed to have the inherent ability to detect the chemical changes associated with the onset of corrosion and respond autonomously to indicate it and control it. The multi-functionality of the coating is based on microencapsulation technology specifically designed for corrosion control applications. This design has, in addition to all the advantages of existing microcapsulation designs, the corrosion controlled release function that triggers the delivery of corrosion indicators and inhibitors on demand, only when and where needed. Microencapsulation of self-healing agents for autonomous repair of mechanical damage to the coating is also being pursued. Corrosion indicators, corrosion inhibitors, as well as self-healing agents, have been encapsulated and dispersed into several paint systems to test the corrosion detection, inhibition, and self-healing properties of the coating. Key words: Corrosion, coating, autonomous corrosion control, corrosion indication, corrosion inhibition, self-healing coating, smart coating, multifunctional coating, microencapsulation.

Calle, Luz M.↗
NASA NTRS1980

A propulsion and steering control system for the Mars rover

The design of a propulsion and steering control system for the Rensselaer Polytechnic Institute prototype autonomous Mars roving vehicle is presented. The vehicle is propelled and steered by four independent electric motors. The control system must regulate the speeds of the motors so they work in unison during turns and on irregular terrain. An analysis of the motor coordination problem on irregular terrain, where each motor must supply a different torque at a different speed is presented. A procedure was developed to match the output of each motor to the varying load. A design for the control system is given. The controller uses a microprocessor which interprets speed and steering commands from an off-board computer, and produces the appropriate drive voltages for the motors.

Turner, J. M.↗
NASA NTRS2012

The Space Operations Simulation Center (SOSC) and Closed-Loop Hardware Testing for Orion Rendezvous System Design

The exploration goals of Orion / MPCV Project will require a mature Rendezvous, Proximity Operations and Docking (RPOD) capability. Ground testing autonomous docking with a next-generation sensor such as the Vision Navigation Sensor (VNS) is a critical step along the path of ensuring successful execution of autonomous RPOD for Orion. This paper will discuss the testing rationale, the test configuration, the test limitations and the results obtained from tests that have been performed at the Lockheed Martin Space Operations Simulation Center (SOSC) to evaluate and mature the Orion RPOD system. We will show that these tests have greatly increased the confidence in the maturity of the Orion RPOD design, reduced some of the latent risks and in doing so validated the design philosophy of the Orion RPOD system. This paper is organized as follows: first, the objectives of the test are given. Descriptions of the SOSC facility, and the Orion RPOD system and associated components follow. The details of the test configuration of the components in question are presented prior to discussing preliminary results of the tests. The paper concludes with closing comments.

Milenkovic, Zoran↗
NASA NTRSDate not supplied

Autonomous Measurement of Electrochemical Redox Couples for In-Situ Characterization of Enceladus Plume Samples

A 3D-printed microfluidic electrochemical cell with integrated electrodes was developed to demonstrate autonomous in-situ electrochemical characterization of terrestrial seawater samples. The system is designed to extend the capabilities of the 2008 Phoenix Lander’s Wet Chemistry Laboratory (WCL) that analyzed the soluble chemistry of the Martian soil, by miniaturizing its fluidic architecture for analysis of µL-volume samples as expected from an Enceladus fly-by mission. The microfluidic device has a total fluid volume of 48 µL and includes dual channels each populated with 7 electrodes. Measurement of pH was measured using an iridium oxide electrode. Cyclic voltammetry with Au, Pt, and glassy carbon working electrodes was used to measure redox couples in synthetic seawater that contained inorganic and bio-organic molecules. Glassy carbon was found to have minimal risk of interference from constituents of synthetic seawater when measuring molecular organic redox species; however, care must be used to prevent interference due to potential oxidation or dissolution in the case of Au working electrodes. A completely autonomous end-to-end run including sample delivery was performed, to demonstrate the feasibility of microfluidic-based cyclic voltammetry measurements for in-situ characterization of redox couples in Ocean World samples.

Planetary Instruments↗
DOE OSTI2020

High precision control and deep learning-based corn stand counting algorithms for agricultural robot

This paper presents high precision control and deep learning-based corn stand counting algorithms for a low-cost, ultra-compact 3D printed and autonomous field robot for agricultural operations. Currently, plant traits, such as emergence rate, biomass, vigor, and stand counting, are measured manually. This is highly labor-intensive and prone to errors. The robot, termed TerraSentia, is designed to automate the measurement of plant traits for efficient phenotyping as an alternative to manual measurements. In this paper, we formulate a Nonlinear Moving Horizon Estimator that identifies key terrain parameters using onboard robot sensors and a learning-based Nonlinear Model Predictive Control that ensures high precision path tracking in the presence of unknown wheel-terrain interaction. Moreover, we develop a machine vision algorithm designed to enable an ultra-compact ground robot to count corn stands by driving through the fields autonomously. The algorithm leverages a deep network to detect corn plants in images, and a visual tracking model to re-identify detected objects at different time steps. We collected data from 53 corn plots in various fields for corn plants around 14 days after emergence (stage V3 - V4). The robot predictions have agreed well with the ground truth with C robot =1.02×C human -0.86 and a correlation coefficient R=0.96. The mean relative error given by the algorithm is -3.78%, and the standard deviation is 6.76%. These results indicate a first and significant step towards autonomous robot-based real-time phenotyping using low-cost, ultra-compact ground robots for corn and potentially other crops.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Advancing specialized biofoundries via automated adaptive laboratory evolution

Adaptive laboratory evolution (ALE) is a powerful strategy for improving microbial phenotypes by harnessing natural selection under defined environmental conditions. Through applying selection regimes, beneficial mutations accumulate, enabling the generation of strains with enhanced properties. However, conventional ALE is labor-intensive and difficult to scale, limiting reproducibility and broader discovery of evolutionary principles. Recent advances in robotics, automation, and computational infrastructure are transforming ALE into a scalable, data-rich experimental paradigm. Automated platforms enable standardized and complex protocols, real-time monitoring, and highly parallel evolution campaigns, improving consistency while generating longitudinal datasets that reveal convergent adaptive mechanisms. Here, we discuss the role of specialized biofoundries in advancing automated ALE and enabling large-scale evolutionary engineering. We review major automated ALE formats and outline key design principles for effective ALE biofoundries, highlighting how automated ALE can support autonomous experimentation and AI-guided strain engineering.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1982

A study of the selection of microcomputer architectures to automate planetary spacecraft power systems

Performance and reliability models of alternate microcomputer architectures as a methodology for optimizing system design were examined. A methodology for selecting an optimum microcomputer architecture for autonomous operation of planetary spacecraft power systems was developed. Various microcomputer system architectures are analyzed to determine their application to spacecraft power systems. It is suggested that no standardization formula or common set of guidelines exists which provides an optimum configuration for a given set of specifications.

Nauda, A.↗
NASA NTRS1991

Integrating CLIPS applications into heterogeneous distributed systems

SOCIAL is an advanced, object-oriented development tool for integrating intelligent and conventional applications across heterogeneous hardware and software platforms. SOCIAL defines a family of 'wrapper' objects called agents, which incorporate predefined capabilities for distributed communication and control. Developers embed applications within agents and establish interactions between distributed agents via non-intrusive message-based interfaces. This paper describes a predefined SOCIAL agent that is specialized for integrating C Language Integrated Production System (CLIPS)-based applications. The agent's high-level Application Programming Interface supports bidirectional flow of data, knowledge, and commands to other agents, enabling CLIPS applications to initiate interactions autonomously, and respond to requests and results from heterogeneous remote systems. The design and operation of CLIPS agents are illustrated with two distributed applications that integrate CLIPS-based expert systems with other intelligent systems for isolating and mapping problems in the Space Shuttle Launch Processing System at the NASA Kennedy Space Center.

Adler, Richard M.↗
NASA NTRS2009

Autonomous Instrument Placement for Mars Exploration Rovers

Autonomous Instrument Placement (AutoPlace) is onboard software that enables a Mars Exploration Rover to act autonomously in using its manipulator to place scientific instruments on or near designated rock and soil targets. Prior to the development of AutoPlace, it was necessary for human operators on Earth to plan every motion of the manipulator arm in a time-consuming process that included downlinking of images from the rover, analysis of images and creation of commands, and uplinking of commands to the rover. AutoPlace incorporates image analysis and planning algorithms into the onboard rover software, eliminating the need for the downlink/uplink command cycle. Many of these algorithms are derived from the existing groundbased image analysis and planning algorithms, with modifications and augmentations for onboard use.

Leger, P. Chris↗
NASA NTRS2014

Tuning Monotonic Basin Hopping: Improving the Efficiency of Stochastic Search as Applied to Low-Thrust Trajectory Optimization

Trajectory optimization methods using MBH have become well developed during the past decade. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing RVs from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by Englander significantly improves MBH performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness, where efficiency is finding better solutions in less time, and robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive RWs originally developed in the field of statistical physics.

mission design↗
NASA NTRS2018

NASA's Learn-to-Fly Project Overview

Learn-to-Fly (L2F) is an advanced technology development effort aimed at assessing the feasibility of real-time, self-learning flight vehicles. Specifically, research has been conducted on merging real-time aerodynamic modeling, learning adaptive control, and other disciplines with the goal of using this “learn to fly” methodology to replace the current iterative vehicle development paradigm, substantially reducing the typical ground and flight testing requirements for air vehicle design. Recent activities included an aggressive flight test program with unique fully autonomous fight test vehicles to rapidly advance L2F technology. This paper presents an overview of the project and key components.

Heim, Eugene H. D.↗
NASA NTRS2022

Should’ve Could’ve: Progress in the Systems Engineering of the Mars2020 On-Board Planner

Mars rover operations has traditionally controlled behavior using meticulously compiled, so-called “Master” sequences that enforce deterministic timing and ordering of activities. While the approach is effective at managing risk and complexity, it can also be inefficient. Extended operations of the Mars2020 rover envisions a fundamentally different scheduling and execution approach. Atomic activities are constrained by mission operators in time, resource usage, and a structure of dependencies. The rover flight software will create and re-create schedules, responding to available energy, data volume, actual activity durations and execution status, observed temperatures, and other on-board state. Schedules are expected to change substantially in the course of execution. The solution space is prohibitively large and probabilistic in nature. A range of emergent behavior is accessible depending on the interaction between actual on-board state and a given formulation of constraints. For years, the specification and implementation of this capability have been considered and refined, as testing and analysis have mapped the contours of the system. Many concepts that could have been adopted were rejected, and in some cases, emergent properties have been exposed and beaten back with approaches to steer the behavior. This paper discusses some of the design history and underlying reasoning in the systems engineering of the first autonomous activity planner on Mars.

Kuhn, Stephen R↗
NASA NTRSDate not supplied

Dynamic Assurance of Autonomous Systems through Ground Control Software∗

Assurance cases are being increasingly acknowledged as a way to build trust in complex systems with autonomous capabilities [1]. An assurance case is a comprehensive, defensible, and valid justification that a system will function as intended for the specific mission and operating environment. Such justifications for systems with autonomous capabilities are often based on various probabilistic quantifications [2]. Due to the dynamic nature of the environmental conditions in which these systems operate, as well as the changing nature of the autonomous systems themselves, these probabilistic quantifications cannot be simply estimated once during design time. Rather, they need to be continually evaluated during systems operations to ensure that the assurance case justifications are valid. We refer to the assurance case that combines both the static and dynamic elements as a Dynamic Assurance Case (DAC).

dynamic assurance case↗
DOE OSTI2021

Comprehension of Spatial Constraints by Neural Logic Learning from a Single RGB-D Scan

Autonomous industrial assembly relies on the precise measurement of spatial constraints as designed by computer-aided design (CAD) software such as SolidWorks. This paper proposes a framework for an intelligent industrial robot to understand the spatial constraints for model assembly. An extended generative adversary network (GAN) with a 3D long short-term memory (LSTM) network was designed to composite 3D point clouds from a single RGB-D scan. The spatial constraints of the segmented point clouds are identified by a neural-logic network that incorporates general knowledge of spatial constraints in terms of first-order logic. The model was designed to comprehend a complete set of spatial constraints that are consistent with industrial CAD software, including left, right, above, below, front, behind, parallel, perpendicular, concentric, and coincident relations. The accuracy of 3D model composition and spatial constraint identification was evaluated by the RGB-D scans and 3D models in the ABC dataset. The proposed model achieved 57.23% intersection over union (IoU) in 3D model composition, and over 99% in comprehending all spatial constraints.

Wang, Dali↗