Results for “autonomous systems robust execution” — Page 2

NASA NTRS2016

Sylph - A SmallSat Probe Concept Engineered to Answer Europa's Big Question

Europa, the Galilean satellite second from Jupiter, contains a vast, subsurface ocean of liquid water. Recent observations indicate possible plume activity. If such a plume expels ocean water into space as at Enceladus, a spacecraft could directly sample the ocean by analyzing the plume’s water vapor, ice, and grains. Due to Europa’s strong gravity, such sampling would have to be done within 5 km of the surface to sample ice grains larger than 5 µm, expected to be frozen ocean spray and thus to contain non-volatile species critical to a biosignature-detection mission. By contrast, the planned Europa Multiple Flyby Mission’s closest planned flyby altitude is 25 km. Sylph is a concept for a SmallSat free-flyer probe that, deployed from the planned Europa Mission, would directly sample the large grains by executing a single ~2-km altitude plume pass. The 40-kg probe would be deployed by the Europa mission just before it executes a plume fly-through. Within the probe’s 16-hour lifespan, it would autonomously navigate to perform a parallel, simultaneous pass at the lower altitude. The Sylph flight system design concept combines SmallSat technologies with robust traditional components and advanced manufacturing technologies. Its payload would comprise Mini-SUDA (SUrface Dust Mass Analyzer), a dual-channel, miniature impact ionization mass spectrometer. Sylph represents a novel type of SmallSat concept: purpose-built configuration, optimized for the harsh environment at Europa and for planetary-protection requirements, and hybridized from both mainstream and SmallSat components.

Imken, Travis↗

NASA NTRS2004

Overview of Intelligent Systems and Operations Development

To achieve NASA's ambitious mission objectives for the future, aircraft and spacecraft will need intelligence to take the correct action in a variety of circumstances. Vehicle intelligence can be defined as the ability to "do the right thing" when faced with a complex decision-making situation. It will be necessary to implement integrated autonomous operations and low-level adaptive flight control technologies to direct actions that enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. This paper will describe the array of technologies required to meet these complex objectives. This includes the integration of high-level reasoning and autonomous capabilities with multiple subsystem controllers for robust performance. Future intelligent systems will use models of the system, its environment, and other intelligent agents with which it interacts. They will also require planners, reasoning engines, and adaptive controllers that can recommend or execute commands enabling the system to respond intelligently. The presentation will also address the development of highly dependable software, which is a key component to ensure the reliability of intelligent systems.

Pallix, Joan↗

NASA NTRS2022

Validation of the Mars 2020 Fault Protection Design: Navigating the Infinity of the Off-Nominal

On July 30th 2020, the Mars 2020 mission successfully launched out of Cape Canaveral, Florida, passed through the Earth’s shadow, and began its short cruise to Mars. Less than seven months later, the Perseverance rover touched down safely in Jezero Crater to begin its ambitious mission that includes looking for signs of ancient life and collecting samples for future return to Earth. Getting to the successful landing, or “Tango Delta Nominal,” could not have been achieved without also considering the off-nominal. One of the teams supporting this ambitious mission is the fault protection (FP) team. This team is tasked with assessing the various failures, or faults, that could prevent mission success and with ensuring that the autonomous behaviors built into the software and hardware can detect faults and recover the vehicle to a safe state. As part of its charter, the FP team designed a test campaign to provide confidence in the system’s robustness to off-nominal scenarios across all of Mars 2020’s mission phases. The greatest challenge associated with designing such a validation campaign was reducing the infinite number of anomalous scenarios into a finite test suite. In addition, the tests needed to be executed efficiently in order to utilize the team’s limited test venue access, but still needed to maintain a level of rigor that guaranteed confidence in the test outcomes. Given that each test scenario generated massive amounts of data, the team also developed methods for quickly ascertaining whether the autonomous fault protection behaviors maintained vehicle safety in the presence of an anomaly. This paper summarizes the processes that the Mars 2020 fault protection team employed to execute its off-nominal validation campaign. It captures both the methods of generating a suite of off-nominal tests, as well as reducing it to a subset that can be realistically executed within schedule and resource constraints. It also describes the various processes and philosophies that the team utilized to execute the tests efficiently, including creating a standardized procedure template, keeping the test cases modular so that they could be easily interchanged, and capturing common fault injections in a change-controlled database. Finally, it will describe the tools and processes for assessing the test data, focusing in particular on a tool that evaluated vehicle state using “secondary” sources of data to validate that the software had truly configured the spacecraft to the expected safe state.

Morantz, Chaz↗

NASA NTRSDate not supplied

Medicine in the Final Frontier Technologies to Enable Autonomous Prolonged (Field) Care in Space

N: The planning and execution of comprehensive “Prolonged Care” strategies are increasingly considered as fundamental operational concepts within the spheres of both military and non-military expeditionary medicine. Numerous advances in recent years have enabled the decentralization of health-related technology that has empowered medical - and even non-medical providers - to offer quality care farther afield and for increasingly extended periods of separation from traditional support structures. However, the operational concepts behind today’s Prolonged Care paradigms are still largely dependent upon external support, including high-bandwidth telemedicine communications technologies (that allow ready access to centralized expertise), robust resupply pathways, and ultimately, on the timely evacuation of the sick and injured. What would happen if none of these support systems were readily available? Extremely remote Prolonged Care is one of the most significant challenges that the National Aeronautics and Space Administration (NASA) faces when preparing to expand human space exploration beyond the International Space Station (ISS) to deep space including the Moon and Mars. Continuous human presence on the International Space Station (ISS) in low Earth orbit for the past 20 years has demonstrated that indeed medical operations can be successfully executed with continuous real-time communications, frequent resupply missions, and the availability of rapid evacuation options. However, as time-distance factors from Earth increase with our pursuit and changing focus towards deep space missions, these resources and capabilities will no longer be available. As a result, space medicine operations will need to become more autonomous and less dependent upon mission support from Earth – requiring our attention and efforts to build robust capabilities that support the ultimate expression of the term “Prolonged Field Care.”

K R Lehnhardt↗

NASA NTRS2012

Autonomous RPOD Technology Challenges for the Coming Decade

Rendezvous Proximity Operations and Docking (RPOD) technologies are important to a wide range of future space endeavors. This paper will review some of the recent and ongoing activities related to autonomous RPOD capabilities and summarize the current state of the art. Gaps are identified where future investments are necessary to successfully execute some of the missions likely to be conducted within the next ten years. A proposed RPOD technology roadmap that meets the broad needs of NASA's future missions will be outlined, and ongoing activities at OSFC in support of a future satellite servicing mission are presented. The case presented shows that an evolutionary, stair-step technology development program. including a robust campaign of coordinated ground tests and space-based system-level technology demonstration missions, will ultimately yield a multi-use main-stream autonomous RPOD capability suite with cross-cutting benefits across a wide range of future applications.

Naasz, Bo J.↗

NASA NTRS2009

Aerobot Autonomy Architecture

An architecture for autonomous operation of an aerobot (i.e., a robotic blimp) to be used in scientific exploration of planets and moons in the Solar system with an atmosphere (such as Titan and Venus) is undergoing development. This architecture is also applicable to autonomous airships that could be flown in the terrestrial atmosphere for scientific exploration, military reconnaissance and surveillance, and as radio-communication relay stations in disaster areas. The architecture was conceived to satisfy requirements to perform the following functions: a) Vehicle safing, that is, ensuring the integrity of the aerobot during its entire mission, including during extended communication blackouts. b) Accurate and robust autonomous flight control during operation in diverse modes, including launch, deployment of scientific instruments, long traverses, hovering or station-keeping, and maneuvers for touch-and-go surface sampling. c) Mapping and self-localization in the absence of a global positioning system. d) Advanced recognition of hazards and targets in conjunction with tracking of, and visual servoing toward, targets, all to enable the aerobot to detect and avoid atmospheric and topographic hazards and to identify, home in on, and hover over predefined terrain features or other targets of scientific interest. The architecture is an integrated combination of systems for accurate and robust vehicle and flight trajectory control; estimation of the state of the aerobot; perception-based detection and avoidance of hazards; monitoring of the integrity and functionality ("health") of the aerobot; reflexive safing actions; multi-modal localization and mapping; autonomous planning and execution of scientific observations; and long-range planning and monitoring of the mission of the aerobot. The prototype JPL aerobot (see figure) has been tested extensively in various areas in the California Mojave desert.

Elfes, Alberto↗

NASA NTRSDate not supplied

Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.

air traffic control↗

NASA NTRSDate not supplied

Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.

aircraft scheduling,traffic flow management,autono↗

NASA NTRS2005

Probabilistic Reasoning for Plan Robustness

A planning system must reason about the uncertainty of continuous variables in order to accurately project the possible system state over time. A method is devised for directly reasoning about the uncertainty in continuous activity duration and resource usage for planning problems. By representing random variables as parametric distributions, computing projected system state can be simplified in some cases. Common approximation and novel methods are compared for over-constrained and lightly constrained domains. The system compares a few common approximation methods for an iterative repair planner. Results show improvements in robustness over the conventional non-probabilistic representation by reducing the number of constraint violations witnessed by execution. The improvement is more significant for larger problems and problems with higher resource subscription levels but diminishes as the system is allowed to accept higher risk levels.

autonomous planning↗

NASA NTRS2021

Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.

air traffic control↗

NASA NTRS1991

Priority scheme planning for the robust SSM/PMAD testbed

Whenever mixing priorities of manually controlled resources with those of autonomously controlled resources, the space station module power management and distribution (SSM/PMAD) environment requires cooperating expert system interaction between the planning function and the priority manager. The elements and interactions of the SSM/PMAD planning and priority management functions are presented. Their adherence to cooperating for common achievement are described. In the SSM/PMAD testbed these actions are guided by having a system planning function, KANT, which has insight to the executing system and its automated database. First, the user must be given access to all information which may have an effect on the desired outcome. Second, the fault manager element, FRAMES, must be informed as to the change so that correct diagnoses and operations take place if and when faults occur. Third, some element must engage as mediator for selection of resources and actions to be added or removed at the user's request. This is performed by the priority manager, LPLMS. Lastly, the scheduling mechanism, MAESTRO, must provide future schedules adhering to the user modified resource base.

Elges, Michael R.↗

NASA NTRS2000

Robustness via Run-Time Adaptation of Contingent Plans

In this paper, we discuss our approach to making the behavior of planetary rovers more robust for the purpose of increased productivity. Due to the inherent uncertainty in rover exploration, the traditional approach to rover control is conservative, limiting the autonomous operation of the rover and sacrificing performance for safety. Our objective is to increase the science productivity possible within a single uplink by allowing the rover's behavior to be specified with flexible, contingent plans and by employing dynamic plan adaptation during execution. We have deployed a system exhibiting flexible, contingent execution; this paper concentrates on our ongoing efforts on plan adaptation, Plans can be revised in two ways: plan steps may be deleted, with execution continuing with the plan suffix; and the current plan may be merged with an "alternate plan" from an on-board library. The plan revision action is chosen to maximize the expected utility of the plan. Plan merging and action deletion constitute a more conservative general-purpose planning system; in return, our approach is more efficient and more easily verified, two important criteria for deployed rovers.

Bresina, John L.↗

NASA NTRS2018

Independent Configurable Architecture for Reliable Operation of Unmanned Systems with Distributed Onboard Services

This paper presents the development of ICAROUS-2 (Independent Configurable Architecture for Reliable Operation of Unmanned Systems with Distributed Onboard Services), the second generation of a software architecture that integrates several algorithms as distributed onboard services to enable robust autonomous UAS applications. In particular, the ICAROUS architecture defines a framework to perform detect and avoid, geofencing, path monitoring, path planning, and autonomous decision making to ensure safety and mission progress. Most of the core algorithms implemented in ICAROUS are formally verified using an interactive theorem prover. These algorithms are composed together using a plan execution engine, whose operational semantics is formally specified. A description of the integrated architecture, services currently available, and flight test results highlighting the capability of ICAROUS are presented.

Balachandran, Swee↗

NASA NTRS2018

Independent Configurable Architecture for Reliable Operation of Unmanned Systems with Distributed Onboard Services

This paper presents the development of ICAROUS-2 (Independent Configurable Architecture for Reliable Operation of Unmanned Systems with Distributed Onboard Services), the second generation of a software architecture that integrates several algorithms as distributed onboard services to enable robust autonomous UAS applications. In particular, the ICAROUS architecture defines a framework to perform detect and avoid, geofencing, path monitoring, path planning, and autonomous decision making to ensure safety and mission progress. Most of the core algorithms implemented in ICAROUS are formally verified using an interactive theorem prover. These algorithms are composed together using a plan execution engine, whose operational semantics is formally specified. A description of the integrated architecture, services currently available, and flight test results highlighting the capability of ICAROUS are presented.

Balachandran, Swee↗

DOE OSTI2026

Signal Whisperers: Enhancing Wireless Reception Using DRL-Guided Reflector Arrays

This paper presents a multi-agent reinforcement learning (MARL) approach for controlling adjustable metallic reflector arrays to enhance wireless signal reception in non-line-of-sight (NLOS) scenarios. Unlike conventional reconfigurable intelligent surfaces (RIS) that require complex channel estimation, our system employs a centralized training with decentralized execution (CTDE) paradigm where individual agents corresponding to reflector segments autonomously optimize reflector element orientation in three-dimensional space using spatial intelligence based on user location information. Through extensive ray-tracing simulations with dynamic user mobility, the proposed multi-agent beam-focusing framework demonstrates substantial performance improvements over single-agent reinforcement learning baselines, while maintaining rapid adaptation to user movement within one simulation step. Comprehensive evaluation across varying user densities and reflector configurations validates system scalability and robustness. The results demonstrate the potential of learning-based approaches for adaptive wireless propagation control.

deep reinforcement learning↗

NASA NTRSDate not supplied

Stochastic Verification by Analysis for Autonomous Systems Management Architecture (ASMA)

The Gateway Vehicle Systems Manager (VSM) is the top-level of a distributed, hierarchical software control system. VSM is data-driven and will make decisions related to mission, fault, resource management and vehicle control. These attributes combined with a high degree of autonomy make it susceptible to emergent behavior. In order to achieve the high level of confidence needed in this critical system, the VSM team has developed a multifaceted verification strategy employing traditional verification techniques, simulation, model checking, and runtime verification. Individual algorithms are verified using conventional testing and model checking using assume-guarantee contracts. A discrete event-based simulation approach is being developed to verify timelines. This presentation describes an enhancement to the verification approach using analysis to enhance system robustness by detecting and resolving the potential for emergent behavior. The verification by analysis employs a Software in the Loop (SITL) environment with real flight software executing on emulated processors, simulations of vehicle subsystems, flight dynamics, and human inputs. Since the possible input space and configuration data set are too large for exhaustive testing, a Monte Carlo approach is used to cover feasible scenarios, augmented with corner cases and known higher-risk scenarios. A key problem in using Monte Carlo-based system verification is evaluating test results to ensure that system behavior is correct. The presentation describes the approach the VSM team uses to monitor behavior for compliance with predetermined boundaries and to identify anomalous behavior for further analysis. This presentation describes the multi-level systems approach to verification, and the simulation-based layer that covers the feasible state space: 1. Overview of the Gateway VSM 2. Special challenges due to heterogeneous, hierarchical architecture 3. Modeling and simulation environment using flight software and system simulations 4. Developing input sets to ensure state-space coverage 5. Developing model and data configuration sets to ensure model coverage 6. Interpreting results without predetermined outcomes 7. Lessons learned and future work

Verification and Validation↗

DOE OSTI2026

AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentation

The automation of chemical research through self-driving laboratories (SDLs) promises to accelerate scientific discovery, yet the reliability and granular performance of the underlying AI agents remain critical, under-examined challenges. In this work, we introduce AutoLabs, a self-correcting, multi-agent architecture designed to autonomously translate natural-language instructions into executable protocols for a high-throughput liquid handler. The system engages users in dialogue, decomposes experimental goals into discrete tasks for specialized agents, performs tool-assisted stoichiometric calculations, and iteratively self-corrects its output before generating a hardware-ready file. We present a comprehensive evaluation framework featuring five benchmark experiments of increasing complexity, from simple sample preparation to multi-plate timed syntheses. Through a systematic ablation study of 20 agent configurations, we assess the impact of reasoning capacity, architectural design (single- vs. multi-agent), tool use, and self-correction mechanisms. Our results demonstrate that agent reasoning capacity is the most critical factor for success, reducing quantitative errors in chemical amounts (nRMSE) by over 85% in complex tasks. When combined with a multi-agent architecture and iterative self-correction, AutoLabs approaches expert-authored reference procedures on the benchmark (F1-score > 0.89) on challenging multi-plate syntheses. These findings establish a clear blueprint for developing robust and trustworthy AI partners for autonomous laboratories, highlighting the synergistic effects of modular design, advanced reasoning, and self-correction to ensure both performance and reliability in high-stakes scientific applications. Code: https://github.com/pnnl/autolabs

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1989

Multi-level manual and autonomous control superposition for intelligent telerobot

Space telerobots are recognized to require cooperation with human operators in various ways. Multi-level manual and autonomous control superposition in telerobot task execution is described. The object model, the structured master-slave manipulation system, and the motion understanding system are proposed to realize the concept. The object model offers interfaces for task level and object level human intervention. The structured master-slave manipulation system offers interfaces for motion level human intervention. The motion understanding system maintains the consistency of the knowledge through all the levels which supports the robot autonomy while accepting the human intervention. The superposing execution of the teleoperational task at multi-levels realizes intuitive and robust task execution for wide variety of objects and in changeful environment. The performance of several examples of operating chemical apparatuses is shown.

Hirai, Shigeoki↗