Results for “Autonomous Operations” — Page 29

NASA NTRSDate not supplied

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗

NASA NTRSDate not supplied

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach.

Distributed↗

NASA NTRS2023

Exploration Electronic Health Record (xEHR) Techport Entry

Exploration missions beyond low Earth orbit will experience significant communication delays and communication black outs that will necessitate asynchronous, increasingly Earth-independent provision of medical care to onboard crew. In this new paradigm, the Crew Medical Officer (CMO), other Crewmembers, and ground support will have to quickly, efficiently, and independently, view medical data, make decisions, and relay important information. Currently, the NASA electronic health record (EHR) is intended only for ground use and is not accessible to in-mission ISS crew for medical decision support and communication. An EHR capable of providing the crew health data, medical store-and-forward communications, and necessary medical administrative tools is critical in enabling NASA’s standard of healthcare during increasingly autonomous operations. The Exploration Medical Integrated Product Team (XMIPT) project called Medical Exploration Development and Implementation Scoping (MEDIScope) developed and reviewed objectives and concept of operations for an exploration EHR (xEHR) with project stakeholders, developed preliminary high-level requirements, and coordinated the handoff of the project to a design and implementation team at the Johnson Space Center (JSC). This JSC team will develop system requirements for the xEHR with inputs from subject matter experts. Following final requirements development, a team will be chosen to develop the xEHR and to conduct a demonstration on a future exploration vehicle such as Gateway.

MEDIScope↗

NASA NTRSDate not supplied

Integrating Planning, Diagnosis and Execution for Vehicle Systems Management

We describe a prototype Vehicle System Manager (VSM) for NASA’s Gateway, a human-capable spacecraft that will also be capable of autonomous operations. The VSM consists of an execution system, planner, and fault management system, integrated via an over-arching mission management compo- nent. We describe the VSM architecture and each of its com- ponents. We describe a series of use cases, centered on a spacecraft propulsive operation that can fail at different times, for different reasons, and how the VSM detects and responds to these failures. We show the VSM is capable of detecting faults and loss of capability, and subsequently replanning, in the presence of each failure scenario.

Planning↗

NASA NTRSDate not supplied

Microwave AeroGel Volatile Collector (MAGVC) Aerogel and Microwave Radiation Study

The MAGVC is a volatile extraction system that uses microwave radiation to sublimate and collect water trapped in regolith on the lunar surface It is comprised of: - Microwave source (magnetron) - Aerogel-insulated chamber (depicted as a dome) - Volatile storage system (depicted as 4 tanks) - Autonomous operating system

Aerogel↗

NASA NTRSDate not supplied

Lunar Mining and Processing: Considerations for Responsible Space Mining & Connections to Terrestrial Mining

The National Aeronautics and Space Administration (NASA) of the United States of America (US) has initiated the Artemis Moon to Mars program to send astronauts (the first woman and person of color) back to the lunar surface, create a sustainable human lunar exploration program, and lead the first human exploration mission to the Mars surface in the late 2030’s [1]. Besides reinvigorating human exploration beyond low Earth orbit not seen since the Apollo program and enabling new scientific activities and discoveries, a major objective of this program is to characterize the resources that exist on the Moon and Mars, and learn how to utilize them for human exploration and the commercialization of cis-lunar space. Commonly known as In Situ Resource Utilization (ISRU), the search for, acquisition, and processing of resources in space has the potential to greatly reduce the dependency on transporting mission consumables and infrastructure from Earth, thereby reducing mission costs, risks, and dependency on Earth. With the launch of Artemis I in November 2022 and the anticipation of several robotic missions to the Moon under the Commercial Lunar Payload Services (CLPS) program, greater recognition and excitement about NASA’s Artemis program and lunar exploration activities is growing in the public. With the recognition that past statements and concept videos of human exploration of the Moon are actually becoming real, there is also a growing awareness of the possible positive and negative consequences and impacts these exploration activities may have on the Moon and Mars. On the positive side, the development of ISRU and lunar mining and processing can enable and grow lunar surface exploration and cis-lunar commercial activities, as well as provide benefits to terrestrial industries through spin-in and spin-back of advanced technologies and autonomous operations. On the negative side, there is a perception that space mining will impact the lunar surface and environment negatively for science, and that cultural beliefs about the Moon need to be addressed and considered before these operations occur. This paper will begin to explore the potential driving attributes and guidelines that will address how best to maximize the lessons and connections to terrestrial mining to reduce the risk and cost of lunar ISRU and space commercial activities, enhance efforts to achieve the terrestrial ‘mine of the future’, and provide viable markets for space-derived technologies until commercial space mining is established. This paper will also begin to explore the potential driving attributes and guidelines that could address how to minimize the environmental and surface impacts of lunar ISRU and foster ‘responsible’ space mining that can be implemented until more official agreements and treaties are signed. The existing robust mining regulations adopted globally will be used as a basis for this examination and suggestions will be presented to adopt these agreements for use in space mining.

ISRU↗

NASA NTRSDate not supplied

Supercritical Water Oxidation and a Preliminary Concept for Lunar Application

Abstract: Water is a critical resource for crewed space exploration missions and reclamation of aqueous waste streams presents the only long-term viable option. Although early Artemis missions are considering water as part of the payload manifest, it would be extremely advantageous if follow-on missions were supplied—either in total or in part—by a reclamation technology that would operate autonomously between missions. An attractive technology is currently under ongoing research at NASA Glenn Research Center (GRC) that employs a Supercritical Water Oxidation (SCWO) process to destroy all hydrocarbons in the waste stream. Testing of an aqueous waste stream simulant, typical of what is generated on the International Space Station (ISS), has shown reductions in Total Organic Carbon (TOC) of greater than 99% with reactor residence times less than 30 s. Recent effort has been directed toward developing a conceptual design based on the current tubular reactor used in the evaluation of the conversion of SCWO. This conceptual design along with the results of recent SCWO conversion experiments will be presented. Recent design enhancements to achieve shorter residence times along with “production simulation” tests will be presented. The diagnostics used in assessing the extent of the waste conversion include a total organic carbon (TOC) analysis, Raman analyses, and measurements of pH, turbidity, and conductivity. Results obtained from the modified reactor configuration will also be compared to those of the Phase I configuration presented in earlier work.

SCWO↗

NASA NTRSDate not supplied

Runway Sign Classifier: A DAL C Certifiable Machine Learning System

In recent years, the remarkable progress of Machine Learning (ML) technologies within the domain of Artificial Intelligence (AI) systems has presented unprecedented opportunities for the aviation industry, paving the way for further advancements in automation, including the potential for single pilot or fully autonomous operation of large commercial airplanes. However, ML technology faces major incompatibilities with existing airborne certification standards, such as ML model traceability and explainability issues or the inadequacy of traditional coverage metrics. Certification of ML-based airborne systems using current standards is problematic due to these challenges. This paper presents a case study of an airborne system utilizing a Deep Neural Network (DNN) for airport sign detection and classification. Building upon our previous work, which demonstrates compliance with Design Assurance Level (DAL) ”D”, we upgrade the system to meet the more stringent requirements of Design Assurance Level ”C”. To achieve DAL C, we employ an established architectural mitigation technique involving two redundant and dissimilar Deep Neural Networks. The application of novel ML-specific data management techniques further enhances this approach. This work is intended to illustrate how the certification challenges of ML-based systems can be addressed for medium criticality airborne applications.

Flight Software↗

NASA NTRSDate not supplied

Development and Field Test Results of Distributed Ground Sensor Fusion Based Object Tracking

Autonomous operations are a crucial aspect in the context of Advanced Air Mobility and other emerging aviation markets. In order to enable this autonomy, an accurate and detailed understanding of the positions of the various vehicles in the air is necessary. Full localization independent of on-board sensors makes the system suitable for noncooperative vehicles. This paper focuses on the object tracking part that relies on distributed ground-based RF and other sensor fusion, considering specific properties and limitations of different sensor types. Results show satisfactory performance in nominal scenarios with full coverage for some sensor types, but RF signals are challenging because of their nature. This paper includes the results from simulations as well as field tests to support the observations and conclusions.

sensor fusion↗

NASA NTRSDate not supplied

Exploration Atmosphere Demonstration of A Multi-Functional Integrated Medical Device (Tempus Pro)

INTRODUCTION The Exploration Medical Capability (ExMC) element within the Human Research Program and the Exploration Medical Integrated Product Team (XMIPT) within the Mars Campaign Office seek to advance medical system design and risk-informed decision-making for exploration missions. This includes assessment of candidate devices and their compatibility within a variety of increasingly Earth-independent medical scenarios. The Tempus Pro (Remote Diagnostic Technologies, Ltd., Philips Corp., Farnborough, UK) is a commercial-off-the-shelf (COTS), multi-functional integrated medical device capable of vital signs monitoring, with built-in procedure support (iAssist), patient record and telemedicine communication features, and medical imaging (e.g., camera, laryngoscope, ultrasound) that meets multiple exploration medical capability needs. One of several hypobaric atmospheres being considered for exploration vehicles is 8.2 psi with 34% oxygen. To assess the useability of the Tempus Pro in such environments by individuals without formal medical training, the unit was tested in May and June of 2023 at the Johnson Space Center 20-Foot Exploration Atmosphere Chamber in conjunction with the Exploration Atmospheres-2 (EA-2) study. TECHNOLOGY DEMONSTRATION Eight subjects in the EA-2 study were assigned roles as the caregiver or patient – or both in the case of a self-exam – and caregivers were asked to place sensors for 3-Lead ECG, non-invasive blood pressure (NIBP), pulse oximetry (SpO2), and temperature using Tempus Pro’s iAssist. Depending on the procedure, additional tasks included an oropharyngeal exam of the throat with the laryngoscope and capturing ultrasound images of a cardiac subxiphoid view or of the user’s choice from a pre-specified list. Scenarios ranged from remote-guided to fully autonomous operations and surveyed the effectiveness of support, amount of support desired, and importance of support by type (e.g., written crew procedures, iAssist and device guidance, remote console guidance, etc.). Feedback from the subjects and the support personnel was also gathered to inform future designs for training and support and to determine what operations are plausible given different levels of each. An unweighted NASA task load index (TLX) was used to profile the demands of using the device, however the sample size does not support statistics. The research was exploratory in nature and qualitative information was the main goal. Calibration checks on the Tempus Pro were conducted before and after chamber testing to ensure the device was in useable condition. RESULTS All subjects performed their tasks successfully and found the Tempus Pro easy to use with the support provided. The calibration checks outside the chamber showed that the Tempus Pro remained unchanged and measurements inside the chamber were within normal values. Caregivers taking the NASA TLX reported mean scores ≤ 41/100 showing the tasks to be undemanding and less demanding with repeated use (~20/100). Novice users were able to easily connect sensors and take vital signs with the guidance from Tempus Pro’s iAssist feature. For more complex tasks, such as the oropharyngeal exam and ultrasound image acquisition, guidance beyond iAssist was needed, primarily from a supporting physician. Feedback on the importance of support types varied by person and scenario but greater than 50% of the support used by each was non-native to the device. Overall opinions were positive, but the ultrasound users expressed a lack of confidence in their results and 3 out of 4 desired more time, training, or support. Subjects found the sensors to be comfortable and comparable to prior experiences with such devices, except for the blood pressure cuff, which squeezed too tightly for uncomfortably long periods. Many observations provoked discussion, especially regarding ultrasound, that will aide decisions about future demonstrations.

R. S. Miller↗

NASA NTRSDate not supplied

Programable Lead Screw Actuated Self-Leveling Platform – PLSASLP

The programmable lead screw actuated self-leveling platform (PLSASLP) is developed to provide a self-leveling and load bearing foundation required by various autonomously operated planetary surface robotic or deployable systems. PLSASLP is capable of self-leveling from a 15-degree offset to accommodate the landing slope tolerance found on most landers designed to land on the surface of the Moon or Mars.

Iok M Wong↗

NASA NTRSDate not supplied

Study of Advanced Occupant Models to Quantify Injury Risk for eVTOL Vehicles

Urban transportation is currently evolving from traditional ground-based vehicles (cars, taxis, and buses) to include air-based electric vertical take-off and landing (eVTOL) vehicles which can be utilized for on-demand transportation, cargo transport, and emergency services. These new eVTOL vehicles are designed to be small, lightweight, and able to operate autonomously without user intervention. Safety is a big part of eventual eVTOL adoption, however gaps in the consideration of safety features exist. Anthropomorphic test devices (ATDs) are used in aerospace crashworthiness standards to quantify occupant injury risk and develop improved safety designs for emergency landing situations, but the ATDs currently used in aircraft certification requirements were developed many decades ago. Developments have occurred over the years involving ATD technology, which includes a host of newer and more biofidelic ATDs such as the Test Device for Human Occupant Restraint (THOR). Increased computing power has also allowed for detailed computational human body models (HBMs) to be created, such as the Global Human Body Model Consortium (GHBMC). This study aims to assess the capability of both HBMs and new ATD designs to identify injury mechanisms within eVTOL relevant emergency landing conditions. Finite element (FE) analysis was used to expand upon full-scale and seat level impact testing conducted by researchers at the National Aeronautics and Space Administration (NASA) to look at effects of occupant model configurations on prediction of injury. The GHBMC HBM and THOR ATD models were simulated in the seat level test conditions to characterize differences between these advanced assessment tools and traditional ATDs in the isolated seat loading environment. Results identified key differences in the responses from each of the models utilized and compared their impact response in head, neck, and spinal injury metrics. The THOR model identified potential risks for head injuries due to head impacts on the seat, however it predicted lower spinal loads than the other occupant surrogates. The GHBMC showed distinctly different biomechanical responses compared to the ATD. The GHBMC model is much more deformable than the ATDs and it exhibited higher distribution of forces and increased sensitivity to the duration of acceleration pulses. Both models incorporated into this study identified key mechanisms for injury that should be considered for passenger safety in the development of these novel aircraft. In addition, this study demonstrated the value of FE modeling for running a variety of complex human surrogates to identify potential injury mechanisms for consideration in regulation and development of new aircraft. Continued research in this field to improve validation these models will only lead to safer aircraft and more comprehensive safety measures.

Crashworthiness↗

NASA NTRSDate not supplied

Study of Advanced Occupant Models to Quantify Injury Risk for eVTOL Vehicles

Urban transportation is currently evolving from traditional ground-based vehicles (cars, taxis, and buses) to include air-based electric vertical take-off and landing (eVTOL) vehicles which can be utilized for on-demand transportation, cargo transport, and emergency services. These new eVTOL vehicles are designed to be small, lightweight, and able to operate autonomously without user intervention. Safety is a big part of eventual eVTOL adoption, however gaps in the consideration of safety features exist. Anthropomorphic test devices (ATDs) are used in aerospace crashworthiness standards to quantify occupant injury risk and develop improved safety designs for emergency landing situations, but the ATDs currently used in aircraft certification requirements were developed many decades ago. Developments have occurred over the years involving ATD technology, which includes a host of newer and more biofidelic ATDs such as the Test Device for Human Occupant Restraint (THOR). Increased computing power has also allowed for detailed computational human body models (HBMs) to be created, such as the Global Human Body Model Consortium (GHBMC). This study aims to assess the capability of both HBMs and new ATD designs to identify injury mechanisms within eVTOL relevant emergency landing conditions. Finite element (FE) analysis was used to expand upon full-scale and seat level impact testing conducted by researchers at the National Aeronautics and Space Administration (NASA) to look at effects of occupant model configurations on prediction of injury. The GHBMC HBM and THOR ATD models were simulated in the seat level test conditions to characterize differences between these advanced assessment tools and traditional ATDs in the isolated seat loading environment. Results identified key differences in the responses from each of the models utilized and compared their impact response in head, neck, and spinal injury metrics. The THOR model identified potential risks for head injuries due to head impacts on the seat, however it predicted lower spinal loads than the other occupant surrogates. The GHBMC showed distinctly different biomechanical responses compared to the ATD. The GHBMC model is much more deformable than the ATDs and it exhibited higher distribution of forces and increased sensitivity to the duration of acceleration pulses. Both models incorporated into this study identified key mechanisms for injury that should be considered for passenger safety in the development of these novel aircraft. In addition, this study demonstrated the value of FE modeling for running a variety of complex human surrogates to identify potential injury mechanisms for consideration in regulation and development of new aircraft. Continued research in this field to improve validation these models will only lead to safer aircraft and more comprehensive safety measures.

Crashworthiness↗

NASA NTRSDate not supplied

Programable Lead Screw Actuated Self-Leveling Platform – PLSASLP

The programmable lead screw actuated self-leveling platform (PLSASLP) is developed to provide a self-leveling and load bearing foundation required by various autonomously operated planetary surface robotic or deployable systems. PLSASLP is capable of self-leveling from a 15-degree offset to accommodate the landing slope tolerance found on most landers designed to land on the surface of the Moon or Mars.

Iok M Wong↗

NASA NTRSDate not supplied

Laser Beam Welding for in-Space Joining Demonstrated Under Vacuum on the Ground and By Parabolic Flight Experiments

High energy density electron beam welding enabled the first and, to date, only American weld performed in space during the M551 experiment on Skylab in 1973. Though welding is critical to 90% of durable goods manufacturing in America, there is not yet regular and reliable application of welding processes to the In-space Servicing, Assembly, and Manufacturing (ISAM) sector. Fundamental studies are needed to develop basic capabilities and to enhance fundamental process knowledge, which will support follow-on efforts to mature in-space welding for use in commercial, defense, and other aerospace applications. The current work seeks to build on past flights and improve understanding and quantification of materials joining in space conditions using laser beam welding (LBW). LBW offers several advantages over the electron beam welding of Skylab, amongst others: reduced electromagnetic interference, less exposure of operators to ionizing radiation, and flexible delivery through optical fibers supporting unique workpieces and joints. Since there is no orbital laboratory to mature laser beam welding for space, the current effort addresses maturation of laser beam welding through parabolic flights augmented with data collection to enable numerical modeling efforts that capture the physical effects of the space environment. This team has retrofitted an LBW experimental apparatus that can simulate the vacuum and, during a parabolic flight, the reduced gravity & microgravity conditions of in-space welding. A team of Capstone students modified the setup, originally developed by NASA Langley Research Center for electron beam free-form fabrication, to replace its electron gun with a 1 kW, 1070 nm Yb fiber laser. The apparatus was further instrumented with temperature sensing and high-speed welding cameras to monitor and record changes in the thermal state of the workpiece, the melt pool, the laser penetration level, and the development and orientation of spatter & plumes. The system will operate autonomously, demonstrating its utility to uncrewed missions. During upcoming parabolic flight campaigns expected summer 2024, this LBW equipment will weld common aerospace alloys of aluminum, stainless steel, and titanium under conditions representative of the space environment. This data will guide future computational modeling efforts of laser welding in space and help to qualify in-space welding as a viable ISAM technique.

laser beam welding↗

NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗

NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗

NASA NTRSDate not supplied

MEAD In-situ Sampling and Testing at Haughton Crater

The Mars Exploration through Analog-site Drilling (MEAD) project is designed to demonstrate the feasibility and scientific value of robotic drilling missions to Mars in the search for evidence of past or extant life. MEAD conducts high-fidelity field simulations integrating drilling, autonomous operations, and in-situ life-detection and mineralogical instruments. The project tests the Signs of Life Detector (SOLID), proposed for the 2019 Discovery Mars Icebreaker mission, and ARIA (Astronaut Raman Instrument for ISRU and Astrobiology), which provides mineral identification and detects trace organics and volatiles, including indicators of organic thermal maturity. Because current and planned Mars drilling missions operate largely “blind,” MEAD also evaluates the use of drill-induced vibrations recorded by deployed geophones to enable local subsurface mapping for improved targeting of drilling and sampling. In August 2025, MEAD completed its first-year field deployment to Haughton Crater in the Canadian High Arctic, an established Mars impact-crater terrestrial analog site, bringing a Honeybee Robotics TRIDENT drill with applied automation, alongside ARIA, SOLID, and FleetSpace geophones.

Haughton Crater↗