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At least 235 records · Page 13

Best Practices Identified Through the Completion of UAS Flight Demonstrations

After several years of research into Detect and Avoid (DAA) and Command and Control (C2) systems for Unmanned Aircraft Systems (UAS), the National Aeronautics and Space Administration’s (NASA) UAS Integration into the National Airspace System project initiated a focused two-year effort along with the Federal Aviation Administration (FAA) and three industry partners to investigate remaining issues in the specification, test, certification and airspace integration to allow UAS operations in non-segregated airspace. The approach taken had the industry partners propose a flight demonstration approximating a commercial operation, while NASA helped, as needed, the partners through design and test phases and NASA observed interactions with the FAA. During this effort NASA collected best practices intended to be of value to similar UAS endeavors. These best practices can be divided into different sets, including practices that describe the relationship between business considerations to UAS design or describe several UAS development challenges. Another set includes best practices focused on navigating the UAS design and type certification processes. A third set includes best practices that relate to the design of the DAA system. Deploying DAA systems in this timeframe posed unique challenges. Commercial off-the-shelf DAA systems do not exist, necessitating custom development and, for two of the partners, the use of low-size, -weight, and -power (SWaP) sensors not completely specified for DAA. A fourth set of best practices relates to lost-link contingency planning. The final set of best practices relates to the design and testing of C2 systems and obtaining spectrum licenses. The UAS demonstrations were piloted remotely, and for all aspects of flight safety, a C2 system was required to communicate DAA and other UAS subsystem data to the remote pilot and to allow the pilot to issue commands to the vehicle. Throughout the course of this effort, the partners integrated prototype DAA and C2 systems into unmanned aircraft, tested those systems, and laid the groundwork for type certification programs that are expected to continue.

NASA↗

A Generative Control Capability for a Model-based Executive

This paper describes Burton, a core element of a new generation of goal-directed model-based autonomous executives. This executive makes extensive use of component-based declarative models to analyze novel situations and generate novel control actions both at the goal and hardware levels. It uses an extremely efficient online propositional inference engine to efficiently determine likely states consistent with current observations and optimal target states that achieve high level goals. It incorporates a flexible generative control sequencing algorithm within the reactive loop to bridge the gap between current and target states. The system is able to detect and avoid damaging and irreversible situations, After every control action it uses its model and sensors to detect anomalous situations and immediately take corrective action. Efficiency is achieved through a series of model compilation and online policy construction methods, and by exploiting general conventions of hardware design that permit a divide and conquer approach to planning. The paper presents a formal characterization of Burton's capability, develops efficient algorithms, and reports on experience with the implementation in the domain of spacecraft autonomy. Burton is being incorporated as one of the key elements of the Remote Agent core autonomy architecture for Deep Space One, the first spacecraft for NASA's New Millenium program.

Williams, Brian C.↗

SC-228 Inclusion of DAA Warning Alert for TCAS Interoperability

This white paper summarizes NASA research results that have informed Special Committee 228 (SC-228) discussions and decisions regarding the inclusion of a warning-level alert within the detect and avoid (DAA) alerting structure for unmanned aircraft systems (UAS). For UAS, the removal of the pilot from onboard the aircraft has eliminated the ability of the ground-based pilot in command (PIC) to use out-the-window visual information to make judgments about a potential threat of a loss of well clear with another aircraft. As a result, the DAA traffic display will be the primary source of information that the PIC can use to execute the three primary well clear functions: 1) detect a potential loss of well clear, 2) determine a resolution maneuver, and 3) upload that maneuver to the aircraft via the ground control station (GCS). In addition, pilots are required to coordinate with air traffic control (ATC) prior to maneuvering off of their approved flight plan. In determining an appropriate resolution maneuver to avoid a loss of well clear, the PIC must decide both when and how to maneuver, and both the timeliness and the accuracy (i.e., correctness) of the maneuver are critical to reducing the likelihood and/or severity of a loss of well clear. Alerting information is one of three critical components of the DAA display, along with traffic information elements (e.g., relative heading, speed and altitude) and maneuver guidance. Alerting information and maneuver guidance, in particular, have been found to have a significant impact, both statistically and practically, on pilots' ability to avoid and minimize the severity of losses of well clear While all three display components are key to pilots performing the traffic avoidance task of remaining well clear, in general, alerting information provides crucial information about when a resolution maneuver is required while maneuver guidance assists the pilot in determining how best to maneuver. A fundamental task of the DAA alerting system is to provide critical timing information to the pilot about the potential for a loss of well clear with another aircraft. This is done by employing both temporal and spatial thresholds that indicate to the pilot the likelihood and imminence of a loss of well clear. The design of the DAA alerting thresholds is a balancing act between eliciting the desired pilot response in real loss of well clear threat events and reducing excessive, unnecessary, and/or uncoordinated UAS maneuvering within the air traffic environment; larger thresholds, both spatially and temporally, may increase the likelihood of a pilot avoiding a loss of well clear, but it can also increase the frequency of maneuvering - especially in cases where a maneuver is not actually needed to maintain well clear. A series of human in the loop (HITL) simulations have been conducted as part of NASA's Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) project. The purpose of these HITLs has been to provide empirical results in order to inform development of the minimum human-machine interface requirements for the DAA system. This white paper will present those results which provide evidence of a human performance benefit (in terms of response times and ability to remain well clear of other aircraft) of the DAA warning alert both with and without a collision avoidance system on board the aircraft.

TCAS interoperability↗

Rocket sled testing of a prototype terrain-relative navigation system

The next generation of Martian landers (2007 and beyond) will employ a precision soft-landing capability that will make it possible to explore previously inaccessible regions on the surface of Mars. This capability will be enabled by onboard systems that automatically identify and avoid terrain containing steep slopes or rocks exceeding a particular terrain height. JPL is currently developing such a hazard detection and avoidance system; this system will map the landing zone with a scanning laser radar, identify hazards, select a safe landing zone, and then guide the vehicle to the selected landing area. This paper describes how one component of this system-hazard detection-is being tested using a rocket sled and simulated Martian terrain.

lidar↗

UAS Pilot Assessments of Display and Alerting for the Airborne Collision Avoidance System XU

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback on these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS Xu alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

UAS↗

Hazard Boresight Relative Navigation for Safe Lunar Landing

In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.

Stephen R. Steffes↗

Hazard Boresight Relative Navigation for Safe Lunar Landing

In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.

Stephen Steffes↗

Helicopter Pilot Evaluations of the Airborne Collision Avoidance System Xr in a High-Fidelity Motion Simulation

New aircraft and aerial Urban Air Mobility operations require updated technologies to maintain vehicle separation during flight. Specifically, higher-density airspace will need more than traditional air traffic control to keep vehicles well clear of each other and avoid Near Midair Collisions. In response, the Federal Aviation Administration is currently developing the Airborne Collision Avoidance System X (ACAS X) for next-generation air traffic deconfliction, which provides caution-level and warning-level alerts in response to multiple aircraft types. This study recruited six helicopter pilots to fly an electric vertical takeoff and landing vehicle model in simulated operations under Visual Flight Rules (VFR). Flights were accomplished using the high-fidelity Vertical Motion Simulator at the NASA Ames Research Center. Participants controlled the vehicle using two side inceptors and foot rudders. The rotorcraft variant of ACAS X (ACAS Xr) was provided for alerting and guidance during traffic conflicts. Pilots used this system while giving feedback to the researchers through questionnaires, debriefs, and other discussions. Variables of interest to the study were phases of flight (i.e., Cruise, Hover, and Approach) and ACAS Xr configurations: The Collision Avoidance System configuration behaves similarly to current commercial traffic systems used for tactical deconfliction in crewed vehicles, and the Detect and Avoid configuration was developed to provide extra, corrective-level guidance for unmanned aircraft systems. Results showed that pilots found the alerting and guidance from ACAS Xr useful, effective, and acceptable for VFR operations. Certain elements, like speed guidance and text banners, were found to be of no use to the pilots. Hover and Approach scenarios were considered the most difficult for ACAS Xr alerting. Reasons for this difficulty were partially due to learning interference (i.e., overcoming previously learned behavior) and partially due to the vehicle model (i.e., NASA’s Lift Plus Cruise design). Still, alerting-based confounds reveal the need for more development for ACAS Xr during these Hover and Approach flight phases. Study caveats and future projects are discussed.

air taxis↗

Helicopter Pilot Evaluations of the Airborne Collision Avoidance System Xr in a High-Fidelity Motion Simulation

New aircraft and aerial Urban Air Mobility operations require updated technologies to maintain vehicle separation during flight. Specifically, higher-density airspace will need more than traditional air traffic control to keep vehicles well clear of each other and avoid Near Midair Collisions. In response, the Federal Aviation Administration is currently developing the Airborne Collision Avoidance System X (ACAS X) for next-generation air traffic deconfliction, which provides caution-level and warning-level alerts in response to multiple aircraft types. This study recruited six helicopter pilots to fly an electric vertical takeoff and landing vehicle model in simulated operations under Visual Flight Rules (VFR). Flights were accomplished using the high-fidelity Vertical Motion Simulator at the NASA Ames Research Center. Participants controlled the vehicle using two side inceptors and foot rudders. The rotorcraft variant of ACAS X (ACAS Xr) was provided for alerting and guidance during traffic conflicts. Pilots used this system while giving feedback to the researchers through questionnaires, debriefs, and other discussions. Variables of interest to the study were phases of flight (i.e., Cruise, Hover, and Approach) and ACAS Xr configurations: The Collision Avoidance System configuration behaves similarly to current commercial traffic systems used for tactical deconfliction in crewed vehicles, and the Detect and Avoid configuration was developed to provide extra, corrective-level guidance for unmanned aircraft systems. Results showed that pilots found the alerting and guidance from ACAS Xr useful, effective, and acceptable for VFR operations. Certain elements, like speed guidance and text banners, were found to be of no use to the pilots. Hover and Approach scenarios were considered the most difficult for ACAS Xr alerting. Reasons for this difficulty were partially due to learning interference (i.e., overcoming previously learned behavior) and partially due to the vehicle model (i.e., NASA’s Lift Plus Cruise design). Still, alerting-based confounds reveal the need for more development for ACAS Xr during these Hover and Approach flight phases. Study caveats and future projects are discussed.

air taxis↗

Summary report of the Human Factors Committee

Reduced visibility as a human factors problem was studied in terms of the number of lives lost and cost of aircraft accidents and incidents. Human factors in flight through turbulence in detection and avoidance techniques, pilot and crew procedures for handling workloads and distractions caused by turbulence, and aircraft handling techniques for safe flights through turbulence are investigated. Education and training were reviewed in icing problems on aircraft. Pilots failure to recognize and detect wind shear in severe storms is examined. The pilots avoidance of lightning is discussed from the human factors point of view.

Cooper, G. E.↗

Path planning and execution monitoring for a planetary rover

A path planner and an execution monitoring planner that will enable the rover to navigate to its various destinations safely and correctly while detecting and avoiding hazards are described. An overview of the complete architecture is given. Implementation and testbeds are described. The robot can detect unforseen obstacles and take appropriate action. This includes having the rover back away from the hazard and mark the area as untraversable in the in the rover's internal map. The experiments have consisted of paths roughly 20 m in length. The architecture works with a large variety of rover configurations with different kinematic constraints.

Gat, Erann↗

Formal Methods in Air Traffic Management: The Case of Unmanned Aircraft Systems

As the technological and operational capabilities of unmanned aircraft systems (UAS) continue to grow, so too does the need to introduce these systems into civil airspace. Unmanned Aircraft Systems Integration in the National Airspace System is a NASA research project that addresses the integration of civil UAS into non-segregated airspace operations. One of the major challenges of this integration is the lack of an onboard pilot to comply with the legal requirement that pilots see and avoid other aircraft. The need to provide an equivalent to this requirement for UAS has motivated the development of a detect and avoid (DAA) capability to provide the appropriate situational awareness and maneuver guidance in avoiding and remaining well clear of traffic aircraft. Formal methods has played a fundamental role in the development of this capability. This talk reports on the formal methods work conducted under NASA's Safe Autonomous System Operations project in support of the development of DAA for UAS. This work includes specification of low-level and high-level functional requirements, formal verification of algorithms, and rigorous validation of software implementations. The talk also discusses technical challenges in formal methods research in the context of the development and safety analysis of advanced air traffic management concepts.

Munoz, Cesar A.↗

Space Technology Mission Directorate Game Changing Development Program

SPLICE project annual program review presentation. SPLICE Precision Landing and Hazard Avoidance (PL&HA) technologies will improve landing precision by an order of magnitude and enable high-resolution real-time 3-D mapping for hazard detection and avoidance during descent.

Guidance Navigation and Control↗

Adaptive Stress Testing of Collision Avoidance Systems for Small UASs with Deep Reinforcement Learning

The next-generation Airborne Collision Avoidance System for smaller UASs (ACAS sXu) is currently being developed and tested by the Federal Aviation Administration (FAA) to provide detect-and-avoid capability for small unmanned aircraft operating beyond line-of-sight. Due to the complexity and safety-critical nature of the system, safety validation is important not only for the certification of the final system, but also for informing changes during the iterative development process. In this paper, we analyze a prototype of ACAS sXu in simulated aircraft encounters to discover scenarios of small near mid-air collisions (sNMACs), an important safety event in which two aircraft come closer than 50 feet horizontally and 15 feet vertically. Due to the size and complexity of the system as well as rarity of sNMAC events, traditional methods such as Monte Carlo testing often require informed setup and targeting to elicit failures. However, such a dependence on domain knowledge can be incompatible with the independent verification and validation (IV&V) process, the aim of which is to discover unforeseen issues. To address these challenges, we apply an accelerated validation method called adaptive stress testing (AST) to find the most likely sNMAC scenarios without reliance on system introspection. AST uses reinforcement learning to adapt the search towards the most promising areas of the search space as it progresses. We use a state-of-the-art deep reinforcement learning algorithm, proximate policy optimization, to more efficiently search the large and continuous state space. We find that this approach significantly improves the performance of AST compared to a prior approach based on Monte Carlo tree search. We perform experiments using AST to find sNMAC events under various encounter configurations, varying parameters pertaining to dynamics and coordination. Our experiments show AST to be very effective at finding sNMAC scenarios. We summarize our findings, presenting high-level categories of discovered sNMACs and specific examples of encounters in each category.

aircraft collision avoidance↗

Ground-Based Vision Tracker for Advanced Air Mobility and Urban Air Mobility

Advanced Air Mobility (AAM) Air Mobility and Urban Air Mobility (UAM) require aircraft surveillance and monitoring for safety and security. Persistent tracking of flying objects provides Air Traffic Control (ATC) and Air Traffic Management (ATM) continuous coverage and knowledge of the national airspace (NAS). Since there are numerous more AAM and UAM aircraft than commercial aircraft, it will be challenging to utilize the same ATC/ATM architectures. A first step in creating a similar ATC/ATM architecture for AAM/UAM will require ground-based and airborne-based sensors to provide monitoring, which will be difficult in urban environments due to GPS degradation. This paper proposes a vision-based tracking method with static cameras by utilizing image subtraction and blob detection, which avoids adding additional electromagnetic interferences in the environment with sensors such as radar. The ground-based vision tracker (GBVT) outputs the detected objects' azimuth and elevation angles from unmanned aerial system (UAS) flight tests. Future and ongoing work includes sending the detected objects' azimuth and elevation angles as inputs for an extended Kalman filter (EKF) to estimate the position and velocity of the detected object.

distributed sensing↗

Ground-Based Vision Tracker for Advanced Air Mobility and Urban Air Mobility

Advanced Air Mobility (AAM) Air Mobility and Urban Air Mobility (UAM) require aircraft surveillance and monitoring for safety and security. Persistent tracking of flying objects provides Air Traffic Control (ATC) and Air Traffic Management (ATM) continuous coverage and knowledge of the national airspace system (NAS). Given the significant disparity in the number of AAM and UAM aircraft compared to commercial aircraft in the NAS, coupled with the dense AAM/UAM operations in urban environments, employing the existing ATC/ATM architectures poses considerable challenges. A first step in creating a similar ATC/ATM architecture for AAM/UAM will require ground-based and airborne-based sensors to provide monitoring, which will be difficult in urban environments due to GPS degradation. This paper proposes a vision-based tracking method with static cameras by utilizing image subtraction and blob detection, which avoids adding additional electromagnetic interferences in the environment with sensors such as radar. The ground-based vision tracker (GBVT) outputs the detected objects' azimuth and elevation angles from unmanned aerial system (UAS) flight tests. Future and ongoing work includes sending the detected objects' azimuth and elevation angles as inputs for an extended Kalman filter (EKF) to estimate the position and velocity of the detected object.

distributed sensing↗

Integrated Collision Avoidance System for Air Vehicle

Collision with ground/water/terrain and midair obstacles is one of the common causes of severe aircraft accidents. The various data from the coremicro AHRS/INS/GPS Integration Unit, terrain data base, and object detection sensors are processed to produce collision warning audio/visual messages and collision detection and avoidance of terrain and obstacles through generation of guidance commands in a closed-loop system. The vision sensors provide more information for the Integrated System, such as, terrain recognition and ranging of terrain and obstacles, which plays an important role to the improvement of the Integrated Collision Avoidance System.

Lin, Ching-Fang↗