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NASA NTRSDate not supplied

3D Representation of UAV-obstacle Collision Risk Under Off-nominal Conditions

Safe operations of autonomous unmanned aerial vehicles (UAVs) in low-altitude airspace with beyond visual line-of-sight (BVLOS) flights demand robust risk monitoring of airspace as well as of people and property on ground. One of the safety critical factors for UAV flights is the risk of collision with static and dynamic obstacles in proximity to its flight path. This paper presents a detailed formulation of risk of obstacle collision incorporating the effects of off-nominal conditions introduced by component failures, degraded controllability and environmental disturbances such as wind gusts. The risk is represented in terms of a matrix with rows corresponding to the likelihood of occurrence of collision and columns representing severity of collision to the vehicle and surrounding structures. Risk likelihood is generated using a Bayesian Belief Network (BBN) that compiles knowledge from related Failure Modes and Effects Analysis (FMEAs) and Subject Matter Experts (SMEs) to determine the probability of collision based on on-board sensor measurements indicative of vehicle health and controllability. Risk severity is computed utilizing a point-mass 3D kinematic model of the vehicle in presence of wind. The proposed risk factor is demonstrated on real flight data from experimental flights of an octocopter at NASA Langley Research Center in presence of simulated obstacles and wind conditions. Effect of varying wind conditions, level of controllability and obstacle measurement noise on the risk factor is demonstrated. The proposed approach enables risk-informed decision making for timely mitigation of current and future unsafe events in autonomous systems.

risk analysis↗

NASA NTRS1998

A low cost approach to simultaneous orbit, attitude, and rate estimation using an extended Kalman filter

An innovative approach to autonomous attitude and trajectory estimation is available using only magnetic field data and rate data. The estimation is performed simultaneously using an Extended Kalman Filter (EKF), a well known algorithm used extensively in onboard applications. The magnetic field is measured on a satellite by a magnetometer, an inexpensive and reliable sensor flown on virtually all satellites in low earth orbit. Rate data is provided by a gyro, which can be costly. This system has been developed and successfully tested in a post-processing mode using magnetometer and gyro data from 4 satellites supported by the Flight Dynamics Division at Goddard. In order for this system to be truly low cost, an alternative source for rate data must be utilized. An independent system which estimates spacecraft rate has been successfully developed and tested using only magnetometer data or a combination of magnetometer data and sun sensor data, which is less costly than a gyro. This system also uses an EKF. Merging the two systems will provide an extremely low cost, autonomous approach to attitude and trajectory estimation. In this work we provide the theoretical background of the combined system. The measurement matrix is developed by combining the measurement matrix of the orbit and attitude estimation EKF with the measurement matrix of the rate estimation EKF, which is composed of a pseudo-measurement which makes the effective measurement a function of the angular velocity. Associated with this is the development of the noise covariance matrix associated with the original measurement combined with the new pseudo-measurement. In addition, the combination of the dynamics from the two systems is presented along with preliminary test results.

Deutschmann, Julie↗

NASA NTRS1998

A Low Cost Approach to Simultaneous Orbit, Attitude, and Rate Estimation Using an Extended Kalman Filter

An innovative approach to autonomous attitude and trajectory estimation is available using only magnetic field data and rate data. The estimation is performed simultaneously using an Extended Kalman Filter, a well known algorithm used extensively in onboard applications. The magnetic field is measured on a satellite by a magnetometer, an inexpensive and reliable sensor flown on virtually all satellites in low earth orbit. Rate data is provided by a gyro, which can be costly. This system has been developed and successfully tested in a post-processing mode using magnetometer and gyro data from 4 satellites supported by the Flight Dynamics Division at Goddard. In order for this system to be truly low cost, an alternative source for rate data must be utilized. An independent system which estimate spacecraft rate has been successfully developed and tested using only magnetometer data or a combination of magnetometer data and sun sensor data, which is less costly than a gyro. This system also uses an Extended Kalman Filter. Merging the two systems will provide an extremely low cost, autonomous approach to attitude and trajectory estimation. In this work we provide the theoretical background of the combined system. The measurement matrix is developed by combining the measurement matrix of the orbit and attitude estimation EKF with the measurement matrix of the rate estimation EKF, which is composed of a pseudo-measurement which makes the effective measurement a function of the angular velocity. Associated with this is the development of the noise covariance matrix associated with the original measurement combined with the new pseudo-measurement. In addition, the combination of the dynamics from the two systems is presented along with preliminary test results.

Deutschmann, Julie↗

NASA NTRS2014

A Super-Resolution Algorithm for Enhancement of FLASH LIDAR Data: Flight Test Results

This paper describes the results of a 3D super-resolution algorithm applied to the range data obtained from a recent Flash Lidar helicopter flight test. The flight test was conducted by the NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project over a simulated lunar terrain facility at NASA Kennedy Space Center. ALHAT is developing the technology for safe autonomous landing on the surface of celestial bodies: Moon, Mars, asteroids. One of the test objectives was to verify the ability of 3D super-resolution technique to generate high resolution digital elevation models (DEMs) and to determine time resolved relative positions and orientations of the vehicle. 3D super-resolution algorithm was developed earlier and tested in computational modeling, and laboratory experiments, and in a few dynamic experiments using a moving truck. Prior to the helicopter flight test campaign, a 100mX100m hazard field was constructed having most of the relevant extraterrestrial hazard: slopes, rocks, and craters with different sizes. Data were collected during the flight and then processed by the super-resolution code. The detailed DEM of the hazard field was constructed using independent measurement to be used for comparison. ALHAT navigation system data were used to verify abilities of super-resolution method to provide accurate relative navigation information. Namely, the 6 degree of freedom state vector of the instrument as a function of time was restored from super-resolution data. The results of comparisons show that the super-resolution method can construct high quality DEMs and allows for identifying hazards like rocks and craters within the accordance of ALHAT requirements.

Bulyshev, Alexander↗

NASA NTRS1986

Crash response data system for the controlled impact demonstration (CID) of a full scale transport aircraft

NASA Langley's Crash Response Data System (CRDS) which is designed to acquire aircraft structural and anthropomorphic dummy responses during the full-scale transport CID test is described. Included in the discussion are the system design approach, details on key instrumentation subsystems and operations, overall instrumentation crash performance, and data recovery results. Two autonomous high-environment digital flight instrumentation systems, DAS 1 and DAS 2, were employed to obtain research data from various strain gage, accelerometer, and tensiometric sensors installed in the B-720 test aircraft. The CRDS successfully acquired 343 out of 352 measurements of dynamic crash data.

Calloway, Raymond S.↗

NASA NTRS1987

An intelligent training system for payload-assist module deploys

An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The Payload-Assist Module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system has, so far, proven to be a potentially valuable addition to the training tools available for training Flight Dynamics Officers in shuttle ground control. The authors are convinced that the basic structure of PD/ICAT can be extended to form a general architecture for intelligent training systems for training flight controllers and crew members in the performance of complex, mission-critical tasks.

Loftin, R. Bowen↗

NASA NTRS1987

An intelligent training system for payload-assist module deploys

Loftin, R. Bowen↗

NASA NTRS2010

AutoGNC Testbed

A simulation testbed architecture was developed and implemented for the integration, test, and development of a TRL-6 flight software set called Auto- GNC. The AutoGNC software will combine the TRL-9 Deep Impact AutoNAV flight software suite, the TRL-9 Virtual Machine Language (VML) executive, and the TRL-3 G-REX guidance, estimation, and control algorithms. The Auto- GNC testbed was architected to provide software interface connections among the AutoNAV and VML flight code written in C, the G-REX algorithms in MATLAB and C, stand-alone image rendering algorithms in C, and other Fortran algorithms, such as the OBIRON landmark tracking suite. The testbed architecture incorporates software components for propagating a high-fidelity truth model of the environment and the spacecraft dynamics, along with the flight software components for onboard guidance, navigation, and control (GN&C). The interface allows for the rapid integration and testing of new algorithms prior to development of the C code for implementation in flight software. This testbed is designed to test autonomous spacecraft proximity operations around small celestial bodies, moons, or other spacecraft. The software is baselined for upcoming comet and asteroid sample return missions. This architecture and testbed will provide a direct improvement upon the onboard flight software utilized for missions such as Deep Impact, Stardust, and Deep Space 1.

Carson, John M., III↗

NASA NTRS1994

Development of the dynamic motion simulator of 3D micro-gravity with a combined passive/active suspension system

The establishment of those in-orbit operations like 'Rendez-Vous/Docking' and 'Manipulator Berthing' with the assistance of robotics or autonomous control technology, is essential for the near future space programs. In order to study the control methods, develop the flight models, and verify how the system works, we need a tool or a testbed which enables us to simulate mechanically the micro-gravity environment. There have been many attempts to develop the micro-gravity testbeds, but once the simulation goes into the docking and berthing operation that involves mechanical contacts among multi bodies, the requirement becomes critical. A group at the Tokyo Institute of Technology has proposed a method that can simulate the 3D micro-gravity producing a smooth response to the impact phenomena with relatively simple apparatus. Recently the group carried out basic experiments successfully using a prototype hardware model of the testbed. This paper will present our idea of the 3D micro-gravity simulator and report the results of our initial experiments.

Yoshida, Kazuya↗

NASA NTRS2001

Image Mission Attitude Support Experiences

The spin-stabilized Imager for Magnetopause to Aurora Global Exploration (IMAGE) is the National Aeronautics and Space Administration's (NASA's) first Medium-class Explorer Mission (MIDEX). IMAGE was launched into a highly elliptical polar orbit on March 25, 2000 from Vandenberg Air Force Base, California, aboard a Boeing Delta II 7326 launch vehicle. This paper presents some of the observations of the flight dynamics analyses during the launch and in-orbit checkout period through May 18, 2000. Three new algorithms - one algebraic and two differential correction - for computing the parameters of the coning motion of a spacecraft are described and evaluated using in-flight data from the autonomous star tracker (AST) on IMAGE. Other attitude aspects highlighted include support for active damping consequent upon the failure of the passive nutation damper, performance evaluation of the AST, evaluation of the Sun sensor and magnetometer using AST data, and magnetometer calibration.

Ottenstein, N.↗

NASA NTRS2016

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

Neilan, James H.↗

NASA NTRS2002

Simulation and Flight Control of an Aeroelastic Fixed Wing Micro Aerial Vehicle

Micro aerial vehicles have been the subject of continued interest and development over the last several years. The majority of current vehicle concepts rely on rigid fixed wings or rotors. An alternate design based on an aeroelastic membrane wing has also been developed that exhibits desired characteristics in flight test demonstrations, competition, and in prior aerodynamics studies. This paper presents a simulation model and an assessment of flight control characteristics of the vehicle. Linear state space models of the vehicle associated with typical trimmed level flight conditions and which are suitable for control system design are presented as well. The simulation is used as the basis for the design of a measurement based nonlinear dynamic inversion control system and outer loop guidance system. The vehicle/controller system is the subject of ongoing investigations of autonomous and collaborative control schemes. The results indicate that the design represents a good basis for further development of the micro aerial vehicle for autonomous and collaborative controls research.

Waszak, Martin↗

NASA NTRS2019

Real-Time UAV Trajectory Prediction for Safety Monitoring in Low-Altitude Airspace

The rising number of small unmanned aerial vehicles (UAVs) expected in the next decade will enable a new series of commercial, service, and military operations in low altitude airspace as well as above densely populated areas. These operations may include on-demand delivery, medical transportation services, law enforcement operations, traffic surveillance and many more. Such unprecedented scenarios create the need for robust, efficient ways to monitor the UAV state in time to guarantee safety and mitigate contingencies throughout the operations. This work proposes a generalized monitoring and prediction methodology that utilizes realtime measurements of an autonomous UAV following a series of way-points. Two different methods, based on sinusoidal acceleration profiles and high-order splines, are utilized to generate the predicted path. The monitoring approach includes dynamic trajectory re-planning in the event of unexpected detour or hovering of the UAV during flight. It can be further extended to different vehicle types, to quantify uncertainty affecting the state variables, e.g., aerodynamic and other environmental effects, and can also be implemented to prognosticate safety-critical metrics which depend on the estimated flight path and required thrust. The proposed framework is implemented on a simplified, scalable UAV modeling and control system traversing 3D trajectories. Results presented include examples of real-time predictions of the UAV trajectories during flight and a critical analysis of the proposed scenarios under uncertainty constraints.

UAV trajectory prognosis↗

NASA NTRS2014

Applying Motion Constraints Based on Test Data

MSC ADAMS is a simulation software that is used to analyze multibody dynamics. Using user subroutines, it is possible to apply motion constraints to the rigid bodies so that they match the motion profile collected from test data. This presentation describes the process of taking test data and passing it to ADAMS using user subroutines, and uses the Morpheus free-flight 4 test as an example of motion data used for this purpose. Morpheus is the name of a prototype lander vehicle built by NASA that serves as a test bed for various experimental technologies (see backup slides for details) MSC.ADAMS"TM" is used to play back telemetry data (vehicle orientation and position) from each test as the inputs to a 6-DoF general motion constraint (details in backup slides) The MSC.ADAMS"TM" playback simulations allow engineers to examine and analyze flight trajectory as well as observe vehicle motion from any angle and at any playback speed. This facilitates the development of robust and stable control algorithms, increasing reliability and reducing development costs of this developmental engine The simulation also incorporates a 3D model of the artificial hazard field, allowing engineers to visualize and measure performance of the developmental autonomous landing and hazard avoidance technology ADAMS is a multibody dynamics solver. It uses forces, constraints, and mass properties to numerically integrate equations of motion. The ADAMS solver will ask the motion subroutine for position, velocity, and acceleration values at various time steps. Those values must be continuous over the whole time domain. Each degree of freedom in the telemetry data can be examined separately; however, linear interpolation of the telemetry data is invalid, since there will be discontinuities in velocity and acceleration.

Burlone, Michael↗

NASA NTRS2004

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Dufrene, Warren R., Jr.↗

NASA NTRS2015

Urban SAFE50: Modeling, Controlling, and Testing Safe UAS Operations in Low Altitude Settings

The research and development of UAVs (Unmanned Aerial Vehicles) are quickly progressing as industries and hobbyist societies recognize their utility. NASA is focused on the technology development and safety considerations surrounding commercial use of UAVs. Urban SAFE50 (Safe Autonomous Flight Environment within the notional last 50 feet of operation of 55 pound class UAS (Small Unmanned Aircraft Systems)) is focused on the necessary real-time decision algorithms and flight models prevalent in low-altitude, high-density city environments. Construction of on-board controls to respond to motor failure and wind dynamics as well as a database of computational flight models and battery discharge profiles will help policymakers to predict and regulate unmanned aircraft flight safely and effectively.

SAFE↗

NASA NTRS2019

Technical Challenges Associated with In-Air Wingtip Docking of Aircraft in Forward Flight

Autonomous in-air wingtip docking of aircraft offers significant opportunity for system level performance gains for numerous aircraft applications. Several of the technical challenges facing wingtip docking of fixed-wing aircraft are addressed in this paper, including: close proximity aerodynamic coupling; mechanisms and operations for robust docking; and relative state estimation methods. A simulation framework considering the aerodynamics, rigid-body dynamics, and vehicle controls is developed and used to perform docking sensitivity studies for a system of two 5.5% scale NASA Generic Transport Model aircraft. Additionally, proof of- concept testing of a candidate docking mechanism designed to move the primary wingtip vortex inboard suggests the viability of such an approach for achieving robust docking.

Quinlan, Jesse R.↗

NASA NTRS1999

An Integrated Vehicle Modeling Environment

This paper describes an Integrated Vehicle Modeling Environment for estimating aircraft geometric, inertial, and aerodynamic characteristics, and for interfacing with a high fidelity, workstation based flight simulation architecture. The goals in developing this environment are to aid in the design of next generation intelligent fight control technologies, conduct research in advanced vehicle interface concepts for autonomous and semi-autonomous applications, and provide a value-added capability to the conceptual design and aircraft synthesis process. Results are presented for three aircraft by comparing estimates generated by the Integrated Vehicle Modeling Environment with known characteristics of each vehicle under consideration. The three aircraft are a modified F-15 with moveable canards attached to the airframe, a mid-sized, twin-engine commercial transport concept, and a small, single-engine, uninhabited aerial vehicle. Estimated physical properties and dynamic characteristics are correlated with those known for each aircraft over a large portion of the flight envelope of interest. These results represent the completion of a critical step toward meeting the stated goals for developing this modeling environment.

Totah, Joseph J.↗