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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

The procedure safety system

Telerobotic operations, whether under autonomous or teleoperated control, require a much more sophisticated safety system than that needed for most industrial applications. Industrial robots generally perform very repetitive tasks in a controlled, static environment. The safety system in that case can be as simple as shutting down the robot if a human enters the work area, or even simply building a cage around the work space. Telerobotic operations, however, will take place in a dynamic, sometimes unpredictable environment, and will involve complicated and perhaps unrehearsed manipulations. This creates a much greater potential for damage to the robot or objects in its vicinity. The Procedural Safety System (PSS) collects data from external sensors and the robot, then processes it through an expert system shell to determine whether an unsafe condition or potential unsafe condition exists. Unsafe conditions could include exceeding velocity, acceleration, torque, or joint limits, imminent collision, exceeding temperature limits, and robot or sensor component failure. If a threat to safety exists, the operator is warned. If the threat is serious enough, the robot is halted. The PSS, therefore, uses expert system technology to enhance safety thus reducing operator work load, allowing him/her to focus on performing the task at hand without the distraction of worrying about violating safety criteria.

Obrien, Maureen E.↗
NASA NTRS2022

Unique Science from the Moon in the Artemis Era

Since the beginning of the space age, the Moon has been proposed as a platform for astronomy. The Moon provides unique capabilities for astrophysics observations. NASA’s Artemis plan to return humans to the Moon in the mid-2020s in a sustainable manner provides an opportunity to advance synergistic approaches between human and robotic exploration. This NASA Engineering and Safety Center (NESC) workshop assesses the feasibility and value proposition of using the Moon as a location for performing unique science observations, leveraging Artemis-era infrastructure while evaluating risks and key engineering challenges.

NASA Engineering and Safety Center↗
NASA NTRS2017

Technology and Tool Development to Support Safety and Mission Assurance

The Assurance Case approach is being adopted in a number of safety-mission-critical application domains in the U.S., e.g., medical devices, defense aviation, automotive systems, and, lately, civil aviation. This paradigm refocuses traditional, process-based approaches to assurance on demonstrating explicitly stated assurance goals, emphasizing the use of structured rationale, and concrete product-based evidence as the means for providing justified confidence that systems and software are fit for purpose in safely achieving mission objectives. NASA has also been embracing assurance cases through the concepts of Risk Informed Safety Cases (RISCs), as documented in the NASA System Safety Handbook, and Objective Hierarchies (OHs) as put forth by the Agency's Office of Safety and Mission Assurance (OSMA). This talk will give an overview of the work being performed by the SGT team located at NASA Ames Research Center, in developing technologies and tools to engineer and apply assurance cases in customer projects pertaining to aviation safety. We elaborate how our Assurance Case Automation Toolset (AdvoCATE) has not only extended the state-of-the-art in assurance case research, but also demonstrated its practical utility. We have successfully developed safety assurance cases for a number of Unmanned Aircraft Systems (UAS) operations, which underwent, and passed, scrutiny both by the aviation regulator, i.e., the FAA, as well as the applicable NASA boards for airworthiness and flight safety, flight readiness, and mission readiness. We discuss our efforts in expanding AdvoCATE capabilities to support RISCs and OHs under a project recently funded by OSMA under its Software Assurance Research Program. Finally, we speculate on the applicability of our innovations beyond aviation safety to such endeavors as robotic, and human spaceflight.

Mission Assuranc↗
NASA NTRS2004

A Software Architecture for Semiautonomous Robot Control

A software architecture has been developed to increase the safety and effectiveness with which tasks are performed by robots that are capable of functioning autonomously but sometimes are operated under control by humans. The control system of such a robot designed according to a prior software architecture has no way of taking account of how the environment has changed or what parts of a task were performed during an interval of control by a human, so that errors can occur (and, hence, safety and effectiveness jeopardized) when the human relinquishes control. The present architecture incorporates the control, task-planning, and sensor-based-monitoring features of typical prior autonomous-robot software architectures, plus features for updating information on the environment and planning of tasks during control by a human operator in order to enable the robot to track the actions taken by the operator and to be ready to resume autonomous operation with minimal error. The present architecture also provides a user interface that presents, to the operator, a variety of information on the internal state of the robot and the status of the task.

Kortenkamp, David↗
NASA NTRS1994

Stereoscopic, Force-Feedback Trainer For Telerobot Operators

Computer-controlled simulator for training technicians to operate remote robots provides both visual and kinesthetic virtual reality. Used during initial stage of training; saves time and expense, increases operational safety, and prevents damage to robots by inexperienced operators. Computes virtual contact forces and torques of compliant robot in real time, providing operator with feel of forces experienced by manipulator as well as view in any of three modes: single view, two split views, or stereoscopic view. From keyboard, user specifies force-reflection gain and stiffness of manipulator hand for three translational and three rotational axes. System offers two simulated telerobotic tasks: insertion of peg in hole in three dimensions, and removal and insertion of drawer.

Kim, Won S.↗
NASA NTRS2011

Safety-Critical Partitioned Software Architecture: A Partitioned Software Architecture for Robotic

The flight software on virtually every mission currently managed by JPL has several major flaws that make it vulnerable to potentially fatal software defects. Many of these problems can be addressed by recently developed partitioned operating systems (OS). JPL has avoided adopting a partitioned operating system on its flight missions, primarily because doing so would require significant changes in flight software design, and the risks associated with changes of that magnitude cannot be accepted by an active flight project. The choice of a partitioned OS can have a dramatic effect on the overall system and software architecture, allowing for realization of benefits far beyond the concerns typically associated with the choice of OS. Specifically, we believe that a partitioned operating system, when coupled with an appropriate architecture, can provide a strong infrastructure for developing systems for which reusability, modifiability, testability, and reliability are essential qualities. By adopting a partitioned OS, projects can gain benefits throughout the entire development lifecycle, from requirements and design, all the way to implementation, testing, and operations.

(Avionics Application Standard Software Interface ↗
DOE OSTI2026

ARCH Technology Snapshot Autonomous Robot Control Hierarchy (ARCH): A universal software system that removes the need to rebuild robotic software for every new platform or task

Robots are increasingly used to perform repetitive, hazardous, and time-sensitive tasks, improving safety and operational efficiency. However, most robotic systems remain difficult to adapt because they are tightly tied to specific hardware and require extensive reprogramming for each new configuration.

42 ENGINEERING↗
NASA NTRS1990

A real-time robot arm collision detection system

A data structure and update algorithm are presented for a prototype real time collision detection safety system for a multi-robot environment. The data structure is a variant of the octree, which serves as a spatial index. An octree recursively decomposes 3-D space into eight equal cubic octants until each octant meets some decomposition criteria. The octree stores cylspheres (cylinders with spheres on each end) and rectangular solids as primitives (other primitives can easily be added as required). These primitives make up the two seven degrees-of-freedom robot arms and environment modeled by the system. Octree nodes containing more than a predetermined number N of primitives are decomposed. This rule keeps the octree small, as the entire environment for the application can be modeled using a few dozen primitives. As robot arms move, the octree is updated to reflect their changed positions. During most update cycles, any given primitive does not change which octree nodes it is in. Thus, modification to the octree is rarely required. Incidents in which one robot arm comes too close to another arm or an object are reported. Cycle time for interpreting current joint angles, updating the octree, and detecting/reporting imminent collisions averages 30 milliseconds on an Intel 80386 processor running at 20 MHz.

Shaffer, Clifford A.↗
NASA NTRS2003

A new method to evaluate human-robot system performance

One of the key issues in space exploration is that of deciding what space tasks are best done with humans, with robots, or a suitable combination of each. In general, human and robot skills are complementary. Humans provide as yet unmatched capabilities to perceive, think, and act when faced with anomalies and unforeseen events, but there can be huge potential risks to human safety in getting these benefits. Robots provide complementary skills in being able to work in extremely risky environments, but their ability to perceive, think, and act by themselves is currently not error-free, although these capabilities are continually improving with the emergence of new technologies. Substantial past experience validates these generally qualitative notions. However, there is a need for more rigorously systematic evaluation of human and robot roles, in order to optimize the design and performance of human-robot system architectures using well-defined performance evaluation metrics. This article summarizes a new analytical method to conduct such quantitative evaluations. While the article focuses on evaluating human-robot systems, the method is generally applicable to a much broader class of systems whose performance needs to be evaluated.

Space Flight/instrumentation↗
DOE OSTI2025

Safe Physics-Informed Machine Learning for Dynamics and Control

This tutorial paper focuses on safe physics-informed machine learning in the context of dynamics and control, providing a comprehensive overview of how to integrate physical models and safety guarantees. As machine learning techniques enhance the modeling and control of complex dynamical systems, ensuring safety and stability remains a critical challenge, especially in safety-critical applications like autonomous vehicles, robotics, medical decision-making, and energy systems. We explore various approaches for embedding and ensuring safety constraints, including structural priors, Lyapunov and Control Barrier Functions, predictive control, projections, and robust optimization techniques. Additionally, we delve into methods for uncertainty quantification and safety verification, including reachability analysis and neural network verification tools, which help validate that control policies remain within safe operating bounds even in uncertain environments. The paper includes illustrative examples demonstrating the implementation aspects of safe learning frameworks that combine the strengths of data-driven approaches with the rigor of physical principles, offering a path toward the safe control of complex dynamical systems.

Drgona, Jan↗
DOE OSTI2023

Motion Planning Algorithms for Safety and Quantum Computing Efficiency

Motion planning remains a fundamental problem in robotics. Sampling-based algorithms use randomization to allow efficient solutions to this complex problem. As mobile robots and autonomous vehicles become more prevalent in everyday life, motion planning must be applied to increasingly challenging scenarios. Safety has become a paramount concern in motion planning for ensuring robotic applications enrich human lives. To date, many motion planning techniques to increase safety in the face of uncertain and dynamic environments have been developed. This dissertation first addresses distributional safety of Rapidly-Exploring Random Trees (RRT) through our algorithm W-Safe RRT. To acknowledge distributional uncertainty and poor modeling, W-Safe RRT uses the Wasserstein metric to provide a probabilistic bound on the distributional distance between a robot and obstacles. Human-interpretable environmental agent classification allows online safety margin adaptation. We propose and analyze an integrating region method for online classification that increases actor labeling accuracy based on behavioral feature values when compared to state of the art methods. The method performs class assignments based on local maximum likelihood in a created behavioral feature-space, allowing a notion of classification uncertainty. Model-based methods with safety guarantees can quickly become computationally in tractable, especially with multiple agents, higher dimensions, and plentiful unknowns. Sampling based algorithms have been parallelized for computation with multi-core computers and GPUs. We consider the use of quantum algorithms and computers for sampling-based motion planning for the first time. Quantum computing performs operations on superpositions of states and can solve certain problems much more efficiently than classical computers, but introduces previously unseen challenges. With Quantum-RRT, we recast the motion planning problem into a database-search structure and use Quantum Amplitude Amplification to find reachable states in the database with a quadratic performance increase over classical methods. We address two error sources with this method: quantum measurement and quantum oracle errors. We then extend this method to Parallel Quantum-RRT, which uses a manager-worker architecture with multiple parallel quantum workers to increase database search efficiency. We compare algorithm architectures and characterize probabilities of multiple workers finding solutions. Lastly, we test in simulation the quantum algorithms against classical versions in a wide variety of scenarios, concluding that a similar parallelization improvement is to be found in the quantum case as was found in the parallelization of classical RRT.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Robot Tracking of Human Subjects in Field Environments

Future planetary exploration will involve both humans and robots. Understanding and improving their interaction is a main focus of research in the Intelligent Systems Branch at NASA's Johnson Space Center. By teaming intelligent robots with astronauts on surface extra-vehicular activities (EVAs), safety and productivity can be improved. The EVA Robotic Assistant (ERA) project was established to study the issues of human-robot teams, to develop a testbed robot to assist space-suited humans in exploration tasks, and to experimentally determine the effectiveness of an EVA assistant robot. A companion paper discusses the ERA project in general, its history starting with ASRO (Astronaut-Rover project), and the results of recent field tests in Arizona. This paper focuses on one aspect of the research, robot tracking, in greater detail: the software architecture and algorithms. The ERA robot is capable of moving towards and/or continuously following mobile or stationary targets or sequences of targets. The contributions made by this research include how the low-level pose data is assembled, normalized and communicated, how the tracking algorithm was generalized and implemented, and qualitative performance reports from recent field tests.

Graham, Jeffrey↗
DOE OSTI2025

Sim2Real Autonomous Robotic Exploration [Poster]

Autonomous robots offer promising solutions for exploration in environments that are inaccessible or hazardous to humans. Despite this, physical training of such robots is often constrained by safety risks, high cost or limited accessibility. This project presents an end-to-end simulation to reality pipeline leveraging Nvidia Isaac Sim and Boston Dynamics' Spot to enable autonomous navigation in indoor environments. A reinforcement learning policy is first trained using Nvidia Isaac Lab to establish Spot's locomotion pattern. Virtual LiDAR sensors are then integrated to perform SLAM-based navigation using simulated odometry. Finally, the simulated navigation scheme is transferred to a physical Spot robot to inspect and record images of a real-world room by repeating the learnt trajectory. The proposed framework highlights the potential of scalable training in simulation and reliable deployment in physical environments. Future directions include dynamic trajectory generation in unseen and challenging environments and integration of environmental sensing like temperature, radiation or humidity via sensor and material simulation.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Integrated soft snake robot for gamma spectroscopy of radiologically contaminated ducting

Anticipated growth in the number and complexity of nuclear facilities entering the decommissioning phase of their lifespan requires innovative methods of mitigating radiological and safety hazards for workers. Advancements in robotics provide opportunities for remote characterization of radiologically contaminated ducts and pipes, reducing worker exposure. However, the nuclear decommissioning industry has shown a hesitancy in adopting new technology due to concerns regarding capital costs and a lack of demonstration data in representative environments. This work aims to leverage novel soft robotics to develop and demonstrate a sensor-integrated characterization tool for contaminated ducting systems. Two gamma spectrometers – one scintillation-based and one solid-state – were selected and integrated into a pneumatically-actuated snake-like soft robot using stretchable electronic cabling. The robot was then demonstrated at the Idaho National Laboratory’s Critical Infrastructure Test Range Complex. The robot maneuvered through a pseudo-constrained corridor containing several sealed sources and the integrated spectrometers collected spectra at various points along the path of travel. Both spectrometers successfully collected spectra with identifiable, isotope-specific peaks. To evaluate the effect of contamination buildup on the collected spectra, the robot with the integrated scintillation detector was tested using a liquid radioactive source. The resulting spectra showed little detection interference from the liquid contamination; however, a short-lived isotope was used which may not be representative of longer-lived contamination.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2007

Independent Review Support for Phoenix Mars Mission Robotic Arm Brush Motor Failure

The Phoenix Project requested the NASA Engineering and Safety Center (NESC) perform an independent peer review of the Robotic Arm (RA) Direct Current (DC) motor brush anomalies that originated during the Mars Exploration Rover (MER) Project and recurred during the Phoenix Project. The request was to evaluate the Phoenix Project investigation efforts and provide an independent risk assessment. This includes a recommendation for additional work and assessment of the flight worthiness of the RA DC motors. Based on the investigation and findings contained within this report, the IRT concurs with the risk assessment Failure Cause / Corrective Action (FC/CA) by the project, "Failure Effect Rating "3"; Major Degradation or Total Loss of Function, Failure Cause/Corrective Action Rating Currently "4"; Unknown Cause, Uncertainty in Corrective Action."

McManamen, John P.↗
NASA NTRS2009

Tele-Supervised Adaptive Ocean Sensor Fleet

The Tele-supervised Adaptive Ocean Sensor Fleet (TAOSF) is a multi-robot science exploration architecture and system that uses a group of robotic boats (the Ocean-Atmosphere Sensor Integration System, or OASIS) to enable in-situ study of ocean surface and subsurface characteristics and the dynamics of such ocean phenomena as coastal pollutants, oil spills, hurricanes, or harmful algal blooms (HABs). The OASIS boats are extended- deployment, autonomous ocean surface vehicles. The TAOSF architecture provides an integrated approach to multi-vehicle coordination and sliding human-vehicle autonomy. One feature of TAOSF is the adaptive re-planning of the activities of the OASIS vessels based on sensor input ( smart sensing) and sensorial coordination among multiple assets. The architecture also incorporates Web-based communications that permit control of the assets over long distances and the sharing of data with remote experts. Autonomous hazard and assistance detection allows the automatic identification of hazards that require human intervention to ensure the safety and integrity of the robotic vehicles, or of science data that require human interpretation and response. Also, the architecture is designed for science analysis of acquired data in order to perform an initial onboard assessment of the presence of specific science signatures of immediate interest. TAOSF integrates and extends five subsystems developed by the participating institutions: Emergent Space Tech - nol ogies, Wallops Flight Facility, NASA s Goddard Space Flight Center (GSFC), Carnegie Mellon University, and Jet Propulsion Laboratory (JPL). The OASIS Autonomous Surface Vehicle (ASV) system, which includes the vessels as well as the land-based control and communications infrastructure developed for them, controls the hardware of each platform (sensors, actuators, etc.), and also provides a low-level waypoint navigation capability. The Multi-Platform Simulation Environment from GSFC is a surrogate for the OASIS ASV system and allows for independent development and testing of higher-level software components. The Platform Communicator acts as a proxy for both actual and simulated platforms. It translates platform-independent messages from the higher control systems to the device-dependent communication protocols. This enables the higher-level control systems to interact identically with heterogeneous actual or simulated platforms.

Lefes, Alberto↗
NASA NTRS1991

Commercial Capaciflector

A capacitive proximity/tactile sensor with unique performance capabilities ('capaciflector' or capacitive reflector) is being developed by NASA/Goddard Space Flight Center (GSFC) for use on robots and payloads in space in the interests of safety, efficiency, and ease of operation. Specifically, this sensor will permit robots and their attached payloads to avoid collisions in space with humans and other objects and to dock these payloads in a cluttered environment. The sensor is simple, robust, and inexpensive to manufacture with obvious and recognized commercial possibilities. Accordingly, NASA/GSFC, in conjunction with industry, is embarking on an effort to 'spin' this technology off into the private sector. This effort includes prototypes aimed at commercial applications. The principles of operation of these prototypes are described along with hardware, software, modelling, and test results. The hardware description includes both the physical sensor in terms of a flexible printed circuit board and the electronic circuitry. The software description will include filtering and detection techniques. The modelling will involve finite element electric field analysis and will underline techniques used for design optimization.

Vranish, John M.↗