Christopher W. Lum

A Risk Based Paradigm and Model for Unmanned Aerial Systems in the National Airspace

A major focus of current unmanned systems operations is assessing the inherent risk associated with a mission. Efforts to integrate unmanned systems into the national airspace require manufacturers be able to calculate the risk of a mission in terms of human safety. Threats to human safety from midair collisions and ground strikes are the focus of the risk model. The projects intent is to assist in determining applications that leverage the strengths of current unmanned aircraft technology while mitigating the weaknesses so as to meet or exceed the safety and economic viability of manned aircraft. The validity of the risk model is demonstrated by comparison to historical data when available. The intended use of the tool is discussed and risk assessments are presented for several example scenarios. Resources for gathering the required information are surveyed and material is developed to aid a general audience in performing a risk assessment.

Assessing and Estimating Risk of Operating Unmanned Aerial Systems in Populated Areas

In order to operate in the national airspace, an aircraft system must have documentation and analysis to show that it can operate at a satisfactory level of safety. For traditional manned aircraft systems, this is equivalent to operating a reliable system. However with Unmanned Aerial Systems (UAS), a relatively unreliable system can safely be operated provided that the risk to bystanders on the ground is sufficiently low. This paper presents a set of design tools and methodologies which can be used to assess the risk associated with operating an UAS in a potentially populated area. The intended use of the tool is discussed and a risk assessment is provided for an existing UAS.

Autonomous Orbit Coordination for Two Unmanned Aerial Vehicles

This work considers autonomous coordination between two Unmanned Aerial Vehicles in orbit about a target, with the purpose of geo-locating the target. Wind signican tly aects the relative phase angle between the vehicles. Guidance algorithms are investigated to maintain an approximately constant phase angle in wind. A planar-kinematic aircraft model is proposed in which the eects of attitude dynamics and nonlinearities are considered. 1. NOMENCLATURE Course, [rad] Va Airspeed, [m/s] Vg Inertial speed, [m/s] Vo Nominal inertial speed, [m/s] Vw Windspeed, [m/s] p Clock angle, or bearing from orbit center, [rad] Heading, [rad] w Wind direction (from), [rad] ~ V Velocity, [m/s] xN North position [m] yE East position [m] R Radius of orbit, [m] Subscripts w Wind e Earth xed North-East-Down frame (NED) b Body xed frame 1; 2 Vehicle 1; 2

Autonomous Airborne Geomagnetic Surveying and Target Identiflcation

This work considers algorithms for maritime search and surveillance missions. Search and identiflcation of magnetic anomalies are evaluated. A combination of a particle fllter and a neural network are used to identify and classify anomalies. Communication among vehicles is assumed to update a centralized occupancy based map which represents a discretized belief of target locations. Control decisions are based on a nearest neighbor search of the surrounding cells of the occupancy map. Simulation is performed using a planar kinematic model and actual aeromagnetic data.

Search Algorithm for Teams of Heterogeneous Agents with Coverage Guarantees

Amongcommonintelligence,reconnaissance,andsurveillancetasks,searchingforatarget in a complex environment is a problem for which autonomous systems are well suited. This workconsiderstheproblemofsearchingfortargetsusingateamofheterogeneousagents.The systemmaintainsagrid-basedworldmodelwhichcontainsinformationabouttheprobability that a target is located in a given cell of the map. Agents formulate control decisions for a fixed number of time steps using a modular algorithm that allows parameterizations of agent capabilities.This paper investigates a solution that guarantees total map coverage.The control law for each agent does not require explicit knowledge of other agents. This yields a systemwhichisscalabletoalargenumberofvehicles.Theresultingsearchpatternsguarantee an exhaustive search of the map in the sense that all cells will be searched sufficiently to ensure that the probability of a target going unnoticed is driven to zero. Modifications to this algorithm for explicit cooperation between agents is also investigated.

Computational and Experimental Ice Accretions of Large Swept Wings in the Icing Research Tunnel

A comparison of computational and experimental ice accretions is presented for three full-scale leading edge swept-wing models spanning from floor to ceiling in the NASA Glenn Icing Research Tunnel (IRT) at three different spanwise stations of the 65%-scale Common Research Model. Experimental ice shapes were generated on the leading edge of each model for a set of icing conditions, and then digitized with a 3D laser scanner. Computational simulations were done for the same flow and icing conditions of the experiment, utilizing CFD (OVERFLOW 3D RANS) for the flowfield solutions, and LEWICE3D for the 3D ice accretion calculations. Results showed both good ice accretion agreement and the need to further explore and better understand the complex 3D flowfield and ice accretion modeling.

A Modular Algorithm for Exhaustive Map Searching Using Occupancy Based Maps

Searching for a target in a complex environment is a common problem encountered by many autonomous systems. This work considers the problem of searching for targets using a team of heterogeneous agents. The system maintains a grid-based world model which contains information about the probability that a target is located in any given cell of the map. Agents formulate control decisions for a fixed number of time steps using a modular algorithm that allows for individual capabilities and characteristics of individual agents to be encoded in several parameters. This paper investigates one aspect of the search strategy and presents a solution that guarantees total map coverage. The resulting search patterns executed by agents guarantee an exhaustive search of the map in the sense that all cells will be searched sufficiently to ensure that the probability of a target being located in any given cell is driven to zero.

Occupancy Based Map Searching Using Heterogeneous Teams of Autonomous Vehicles

In typical search missions, the environment and the targets are not stationary and previous observations become less reliable as time progresses. In addition, the search is often initiated with only a rough idea of target location. In this work we consider a strategy for searching using a team of heterogeneous autonomous vehicles. The team members maintain a world model which includes the estimate of possible target states. The issue of compelling agents to converge on targets and to search unexplored regions is formulated as a model predictive control problem. The world model is propagated in time and strategic decisions are made autonomously based on its prediction. Agents formulate control decisions by optimizing an objective function which allows for control and timing constraints. Individual agents in the team are coupled to one another through the centralized occupancy based map. This coupling, in combination with the outlined search strategy, leads to an e‐cient, autonomous, and cooperative search.

Time constrained randomized path planning using spatial networks

Real time planning of optimal paths remains an open problem in many applications of autonomous systems. This paper demonstrates a computationally efficient method for generating a set of feasible paths through parameterization into a series of nodes. The nodes and the arcs make up a directed graph. The state of the environment is embedded in an occupancy based map. A notion of optimality is introduced by combining the directed graph with this map. Network optimization techniques are used to find the best path through the directed graph.

Effect of Ice Shape Fidelity on Swept-Wing Aerodynamic Performance

Low-Reynolds number testing was conducted at the 7 ft x 10 ft Walter H. Beech Memorial Wind Tunnel at Wichita State University to study the aerodynamic effects of ice shapes on a swept wing. A total of 17 ice shape configurations of varying geometric detail were tested. Simplified versions of an ice shape may help improve current ice accretion simulation methods and therefore aircraft design, certification, and testing. For each configuration, surface pressure, force balance, and fluorescent mini-tuft data were collected and for a selected subset of configurations oil-flow visualization and wake survey data were collected. A comparison of two ice shape geometries and two configurations with simplified geometric detail for each ice shape geometry is presented in this paper.