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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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NASA NTRS2017

An Integrated System for Autonomous Search and Track with a Small Unmanned Aerial Vehicle

This article presents a framework for searching, detecting, and tracking an object of interest with a small unmanned aerial vehicle (sUAV). The vehicle is given an area to search for an object of interest. Once the object is detected, the sUAV follows the target while maintaining a fixed distance and centered on its image plane. This paper describes an architecture for integrating autonomy capabilities for search and track for sUAVs. The system has been implemented in the Robot Operating System (ROS) framework using the Parrot ARDrone platform. In this paper we present our technical approach, the system architecture and demonstrate the principles of the approach in a simulation environment and indoor flight tests.

Unmanned Aerial Vehicle↗

DOE OSTI2019

Informative Path Planning for Mapping Radiation

This project involves making measurements of contaminated areas using portable radiation detectors and small robots. Tasks involve operating detectors and small robots, combining data acquisition for the two systems, and automating the systems. The end result is a radiation map of contamination areas. Localization of radioactive sources and mapping of contamination distribution is essential when responding to emergencies, or when dealing with cleanup efforts. Radiation maps are used for situational awareness and for establishing a safe perimeter. However, it may be hazardous or impossible for humans to safely enter the site and survey the area. Informative Path Planning (IPP) is used to design a path for a robotic sensor platform to gather the most information about the radiation distribution while operating under the set of constraints given by the dynamics of the robot and other requirements such as minimizing the overall mission time. The key challenge for IPP is the tight coupling in multiple layers of decisions: Selection of locations to visit; Allocation of sensors to those locations; Processing of information gathered. Given a robot equipped with a basic gamma detector and Lidar sensor, how can we efficiently explore an unknown environment in such a way that we can satisfy the robot's constraints while simultaneously maximizing the accuracy of the map and minimizing the total runtime? This work presents a systematic procedure for IPP and environmental mapping that: Selects the best locations at which to sample; Finds the best path for robots; Estimates the measurement value at unknown locations using a Gaussian Process regression framework. Given a set of points where radiation measurements were taken, we are utilizing a Gaussian Process Regression with a Matern kernel to reconstruct the shape of the underlying ground truth. Mapping is done via the Robot Operating System's OpenSlam Gmapping package, which creates a 2D occupancy grid map. Simulated trials were run with a radiation source placed at random locations, and allowing the robot to select and move towards 20 samples at separate locations, as well as sampling along the path while moving. The simulated sensor model assumed an efficiency of 0.3, collection time of 1 second. Various weighting schemes were tested and compared. Quantitative evaluations often favored exploitation-heavy weighting schemes where μ was emphasized, with the Root Mean Squared Error (RMSE) quickly tending towards 2, whereas qualitative comparisons would favor exploration-biased schemes with greater weight on σ. The difference comes from operators often favoring knowing the general location of a source, rather than the exact properties of a source. Weighting of the path-length π often reduced the quality of the regression as less exploration occurred, however this may be deemed a worthwhile trade-off under certain circumstances, such as with sensitive robots. Successfully developed a methodology for informative path-planning for a robot to efficiently gather information and create a map of radiation. In the future, we would like to focus on: Hardware trials with integration of the robot platform and the IPP software; More refined sensor and environmental modeling; Multiple robot platforms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1987

Development of a semi-autonomous service robot with telerobotic capabilities

The importance to the United States of semi-autonomous systems for application to a large number of manufacturing and service processes is very clear. Two principal reasons emerge as the primary driving forces for development of such systems: enhanced national productivity and operation in environments whch are hazardous to humans. Completely autonomous systems may not currently be economically feasible. However, autonomous systems that operate in a limited operation domain or that are supervised by humans are within the technology capability of this decade and will likely provide reasonable return on investment. The two research and development efforts of autonomy and telerobotics are distinctly different, yet interconnected. The first addresses the communication of an intelligent electronic system with a robot while the second requires human communication and ergonomic consideration. Discussed here are work in robotic control, human/robot team implementation, expert system robot operation, and sensor development by the American Welding Institute, MTS Systems Corporation, and the Colorado School of Mines--Center for Welding Research.

Jones, J. E.↗

NASA NTRS2018

Astrobee Robot Software: A Modern Software System for Space

Astrobee is a new free-flyer robot designed to operate inside the International Space Station (ISS). Astrobee capabilities include markerless navigation, autonomous docking for recharge, perching on handrails to minimize power and modular payloads. Astrobee will operate without crew support, controlled by teleoperation, plan execution, or on-board third parties software. This paper presents the Astrobee Robot Software, a NASA Open-Source project, powering the Astrobee robot. The Astrobee Robot Software relies on a distributed architecture based on the Robot Operating System (ROS). The software runs on three interconnected smart phone class processors. We present the software approach, infrastructure required, and main software components. The Astrobee Robot Software embrace modern software practices while respecting flight constraints. The paper concludes with the lessons learned, including examples usage of the software. Several research teams are already using the Astrobee Robot Software to develop novel projects that will fly on Astrobee.

Astrobee↗

DOE OSTI2024

Mid-IR UAV-based sensing platform with deep learning to Identify and Quantify Gaseous Emission in Gas Flares

This report details the development and evaluation of a Mid-Infrared (Mid-IR) Unmanned Aerial Vehicle (UAV)-based sensing platform integrated with deep learning algorithms for the identification and quantification of gaseous emissions in gas flares. The project, spearheaded by Omega Optics, Inc., aimed to address environmental monitoring challenges by leveraging advanced photonic technologies and autonomous UAV operations. The research focused on designing, optimizing, and fabricating photonic crystal waveguides and grating couplers to enhance the sensitivity and accuracy of gas detection. A comprehensive drone-based system was developed, featuring a miniaturized sensor, GPS module, and microcontroller communication network for real-time gas concentration monitoring. The system's adaptive sampling algorithm, implemented using the Robot Operating System (ROS), enables autonomous detection and localization of gas emission sources. Preliminary results demonstrate the platform's capability to detect and monitor gas emissions with high precision, cost-effectiveness, and scalability. Future work will expand upon this foundation by introducing 3D wind model-based learning for dynamic environmental conditions and further enhancing the user interface and data processing algorithms to support broader environmental monitoring applications. Overall, this project represents a significant step forward in UAV-based environmental sensing technologies, offering robust solutions for detecting and mitigating the impacts of gaseous emissions on public health and safety.

47 OTHER INSTRUMENTATION↗

NASA NTRS2010

Development and Evaluation of Sensor Concepts for Ageless Aerospace Vehicles: Report 6 - Development and Demonstration of a Self-Organizing Diagnostic System for Structural Health Monitoring

This report describes a significant advance in the capability of the CSIRO/NASA structural health monitoring Concept Demonstrator (CD). The main thrust of the work has been the development of a mobile robotic agent, and the hardware and software modifications and developments required to enable the demonstrator to operate as a single, self-organizing, multi-agent system. This single-robot system is seen as the forerunner of a system in which larger numbers of small robots perform inspection and repair tasks cooperatively, by self-organization. While the goal of demonstrating self-organized damage diagnosis was not fully achieved in the time available, much of the work required for the final element that enables the robot to point the video camera and transmit an image has been completed. A demonstration video of the CD and robotic systems operating will be made and forwarded to NASA.

Batten, Adam↗

NASA NTRSDate not supplied

Lunar Excavator Mission Operations using Dynamic Movement Primitives

To support sustainable infrastructure on the Moon, NASA must leverage robots to extract lunar resources for in-situ processing and construction. As part of this effort, NASA is launching the in-situ resource utilization (ISRU) Pilot Excavator later this decade to validate a robotic regolith excavator based on the Regolith Advanced Surface Systems Operations Robot (RASSOR). RASSOR is designed to extract and transport regolith to meet the needs of ISRU architectures. During its mission, Pilot Excavator will be tasked with driving in test patterns to demonstrate the operational concept. One of these tests is a circular trajectory around the lander while avoiding miscellaneous surface hazards such as lunar rocks. To this end, we utilize dynamic movement primitives to represent navigation sequences as primitive trajectories. Here, we introduce a novel obstacle avoidance parameter, which is configured to avoid rocks throughout testing exercises. We demonstrate the effectiveness our method in a newly developed simulation tool called the Simulated Excavation Environment for Lunar Operations (SEELO) using models based on the NASA RASSOR 2.0 excavator. After making key changes to the obstacle avoidance formulation, our results show that the robot is able to safety and robustly navigate the lunar surface with densely populated rock obstacles while retaining the desired circle pattern behavior.

Space Robotics and Automation↗

NASA NTRSDate not supplied

iMETRO (Integrated Mobile Evaluation Testbed for Robotics Operations) Facility

Exploration crew time in space is precious – every hour could yield immense scientific discovery. However, overhead tasks such as logistics, maintenance, and assembly greatly limit crew time available for science and exploration. Robotic remote operations capabilities offer a solution, but operating mobile dexterous robots in human centered environments presents many unknowns and challenges, therefore testing is needed. iMETRO is a NASA JSC robotics test facility for terrestrial robotic technology adaptation for space exploration use cases, including logistics, maintenance, and science utilization. iMETRO focuses on Intra-Vehicular task environments, such as surface habitats, pressurized rover cabins, and space station modules (both Gateway & LEO). Its goal is to advance the Technology Readiness Levels (TRL) of remote space robot operations systems with Earth supervision.

Robotics↗

NASA NTRS1985

The role of robotics in space system operations

The role of automation and robotics in support of man's activities in space is discussed, with emphasis given to satellite servicing functions on board the NASA Space Station (SS) or at remote locations. Consideration is given to four satellite servicing mission scenarios, including: low-earth-orbit (LEO) servicing of satellite in situ or on the Space Station following orbital transfer by means of an Orbital Maneuvering Vehicle (OMV); in situ servicing of a free-flying coorbiting materials processing platform; repair/refurbishment of Space Station payloads of substations; an in situ servicing of geostationary satellites by means of an Orbital Transfer Vehicle (OTV). The potential applications of three different automation technologies are examined, including: teleoperation; robotics; and artificial intelligence. Consideration is also given to the potential applications of the Space Station data system in support of servicing activities. A list of the more common terms of automation technology is provided.

Meissinger, H. F.↗

DOE OSTI2020

Autonomous Radiation Mapping and Quantification using an Unmanned Ground Vehicle. Part I - Environment Mapping

When characterizing facilities, advanced autonomous systems are safe, efficient, and cost-effective tools, which can safely deploy state-of-the-art instrumentation without exposing workers to radiation risks. One main focus of the research is the visual mapping of the environment.This paper presents a framework for the mapping aspect that utilizes lidar and SLAM technologies coupled with a monocular camera to create a point cloud of the environment. Upon completion, the present research work aims to provide an autonomous mobile robot the capability to localize itself and aid the user with visualizing the radiation data. Challenges: C++ node needs to properly synchronize image and point cloud data. 3D lidar has resolution of ± 3 cm. Proper camera calibration needed. Transforms need to be precise for proper alignment of image and point-cloud. Results: Voxelated point clouds. Accurate colors from calibrated cameras including details smaller than lidar resolution. Developed Robotics Operating System (ROS) package for ease of transfer to other robot platforms.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

radkit v1.2

The radkit software suite (python) consists of three primary libraries: stark, trajan, and curie. The trajan library provides the tools to analyze and manipulate data from lidar and inertial measurement unit (IMU) devices as well as trajectories from algorithms such as simultaneous localization and mapping (SLAM). These components allow reading and writing standard data formats, performing rigid affine transformations, discretizing three-dimensional space, and visualizing data products. The curie library comprises a standard set of object-oriented tools for radiation data and analysis in the following modules: (1) listmode and binmode data classes with methods for manipulation, plotting, slicing and file IO; (2) radiological/nuclear source detection/identification analysis results; (3) source encounters of correlated analyses and (4) energy-dependent angular detector response functions. The stark package provides low-level tools that are leveraged by both curie and trajan. The tools are flexible for offline analysis as well as performant for real-time integrations. The radkit libraries have associated Robot Operating System packages for use in real-time and robotic systems.

Joshi, Tenzing↗

NASA NTRS2020

Maintenance-optimized Modular Robotic Concepts for Planetary Surface ISRU Excavators

Modular robotic concepts are identified and evaluatedover the design and operations/maintenance lifecycle forautonomous Lunar, Mars, and partial gravity planetary surfaceexcavation and in-situ earthworks equipment. In-Situ ResourceUtilization (ISRU) is the exploitation of available resources at thesite of a landed spacecraft on the surface of another planetary body.It is intended that this ISRU excavator concept be capable ofmaterial extraction from native regolith, and will be able to operatein a variety of planetary surface environments after initial shakedownon the moon. Using heritage from highly multi-functional,reconfigurable robotic systems like the All-Terrain Hex-LimbedExtra-Terrestrial Explorer (ATHLETE), Regolith AdvancedSurface Systems Operations Robot (RASSOR), and Marsexploration rovers, we propose a flexible maintenance-optimizedmobility platform concept with quick-connect/disconnect featuresfor robotically swappable excavation implements. Dust toleranttorque transmission, power & data docking, thermal fluidconnectors, and modular avionics and instrumentation will allow forautonomous swapping of tools, replacement of spares, and longtermmaintenance of robotic excavators. The architecture includesmodular tools for conventional excavate / scoop / haul / dump /process functions of a terrestrial mining operation on Earth, but alsowill have the capability to operate and robotically maintain itselfwithout human intervention. The concepts described in this studywill provide a suite of technologies, configurations, and operationsready for inclusion into a final flight-ready excavator system.

Schuler, Jason↗

DOE OSTI2022

ROS-Ethereum: A Convenient Tool to Bridge ROS and Blockchain (Ethereum)

Robot Operating System (ROS) has received widespread utilization with the development of robotics, self-driving, etc., recently. Meanwhile, the other technology blockchain is frequently applied to various fields with its trustworthy characteristics and immutability in data storage. However, ROS has no ability to interact with the blockchain, which hinders research in related fields. Therefore, we wonder if we can develop a convenient tool to bridge ROS and blockchain. Inspired by this, we propose ROS-Ethereum. It bridges ROS and Ethereum, a widely used blockchain platform. ROS-Ethereum is based on the User Datagram Protocol (UDP) communication mechanism and the SM algorithm family along with Ethereum technology. Simply put, ROS-Ethereum allows users to invoke the contract when interacting with the blockchain, which makes this process easier and safer. We conduct experiments in real robots to verify the effectiveness of ROS-Ethereum and evaluate it from the following metrics: (1) the encryption efficiency and stability of the algorithm and (2) ROS-Ethereum transaction response time and packet loss rate.

Zhang, Shenhui↗

NASA NTRSDate not supplied

ISRU Pilot Excavator (IPEx) Technology Readiness Level 5 Design Overview

This paper details the mechanical and mechatronic design of the Technology Readiness Level (TRL)-5 In-Situ Resource Utilization (ISRU) Pilot Excavator (IPEx). IPEx is a robotic excavator designed for a technology demonstration of regolith mining in the lunar south -pole region. The novel design uses pairs of counter-acting excavation tools called bucket drums, that dig at the same time in opposing directions to reduce the reaction force needed, thereby enabling mining with a small, low-mass, robotic system. IPEx builds on the prior work of the Regolith Advanced Surface Systems Operations Robot (RASSOR), which is the TRL-4 implementation of this concept. The TRL-5 IPEx subsystems that are discussed in this paper include: Regolith Delivery Subsystem (RDS), Mobility Subsystem (MS), Cameras and Dust Mitigation Subsystem (CDMS), and Thermal Control Subsystem (TCS). Each subsystem is described in detail with rationale for design selections. Dust tolerance is a key feature for IPEx and this paper details a thermal control system with an actuated radiator cover and phase change material as well as camera modules with removable electrodynamic dust shields (EDS). Additional components such as actuators, wheels, and bucket drums are discussed in detail. Due to their complexity, the avionics and software subsystems will be discussed in a separate publication.

RASSOR↗

NASA NTRS1995

On the hitchhiker Robot Operated Materials Processing System: Experiment data system

The Space Shuttle Discovery STS-64 mission carried the first American autonomous robot into space, the Robot Operated Materials Processing System (ROMPS). On this mission ROMPS was the only Hitchhiker experiment and had a unique opportunity to utilize all Hitchhiker space carrier capabilities. ROMPS conducted rapid thermal processing of the one hundred semiconductor material samples to study how micro gravity affects the resulting material properties. The experiment was designed, built and operated by a small GSFC team in cooperation with industry and university based principal investigators who provided the material samples and data interpretation. ROMPS' success presents some valuable lessons in such cooperation, as well as in the utilization of the Hitchhiker carrier for complex applications. The motivation of this paper is to share these lessons with the scientific community interested in attached payload experiments. ROMPS has a versatile and intelligent material processing control data system. This paper uses the ROMPS data system as the guiding thread to present the ROMPS mission experience. It presents an overview of the ROMPS experiment followed by considerations of the flight and ground data subsystems and their architecture, data products generation during mission operations, and post mission data utilization. It then presents the lessons learned from the development and operation of the ROMPS data system as well as those learned during post-flight data processing.

Kizhner, Semion↗

NASA NTRS2004

Planning and Execution: The Spirit of Opportunity for Robust Autonomous Systems

One of the most exciting endeavors pursued by human kind is the search for life in the Solar System and the Universe at large. NASA is leading this effort by designing, deploying and operating robotic systems that will reach planets, planet moons, asteroids and comets searching for water, organic building blocks and signs of past or present microbial life. None of these missions will be achievable without substantial advances in.the design, implementation and validation of autonomous control agents. These agents must be capable of robustly controlling a robotic explorer in a hostile environment with very limited or no communication with Earth. The talk focuses on work pursued at the NASA Ames Research center ranging from basic research on algorithm to deployed mission support systems. We will start by discussing how planning and scheduling technology derived from the Remote Agent experiment is being used daily in the operations of the Spirit and Opportunity rovers. Planning and scheduling is also used as the fundamental paradigm at the core of our research in real-time autonomous agents. In particular, we will describe our efforts in the Intelligent Distributed Execution Architecture (IDEA), a multi-agent real-time architecture that exploits artificial intelligence planning as the core reasoning engine of an autonomous agent. We will also describe how the issue of plan robustness at execution can be addressed by novel constraint propagation algorithms capable of giving the tightest exact bounds on resource consumption or all possible executions of a flexible plan.

Muscettola, Nicola↗

DOE OSTI2016

ROSSTEP v1.3

ROSSTEP is a system for sequentially running roslaunch, rosnode, and bash scripts automatically, for use in Robot Operating System (ROS) applications. The system consists of YAML files which define actions and conditions. A python file parses the code and runs actions sequentially using the sys and subprocess python modules. Between actions, it uses various ROS-based code to check conditions required to proceed, and only moves on to the next action when all the necessary conditions have been met. Included is rosstep-creator, a QT application designed to create the YAML files required for ROSSTEP. It has a nearly one-to-one mapping from interface elements to YAML output, and serves as a convenient GUI for working with the ROSSTEP system.

Allevato, Adam↗

DOE OSTI2016

ROSSTEP v1.3

Allevato, Adam↗