A Learning-Based Guidance Selection Mechanism for a Formally Verified Sense and Avoid Algorithm

This paper describes a learning-based strategy for selecting conflict avoidance maneuvers for autonomous unmanned aircraft systems. The selected maneuvers are provided by a formally verified algorithm and they are guaranteed to solve any impending conflict under general assumptions about aircraft dynamics. The decision-making logic that selects the appropriate maneuvers is encoded in a stochastic policy encapsulated as a neural network. The networks parameters are optimized to maximize a reward function. The reward function penalizes loss of separation with other aircraft while rewarding resolutions that result in minimum excursions from the nominal flight plan. This paper provides a description of the technique and presents preliminary simulation results

UAV as a Reliable Wingman: A Flight Demonstration

In this brief, we present the results from a flight experiment demonstrating two significant advances in software enabled control: optimization-based control using real-time trajectory generation and logical programming environments for formal analysis of control software. Our demonstration platform consisted of a human-piloted F-15 jet flying together with an autonomous T-33 jet. We describe the behavior of the system in two scenarios. In the first, nominal state communications were present and the autonomous aircraft maintained formation as the human pilot flew maneuvers. In the second, we imposed the loss of high-rate communications and demonstrated an autonomous safe “lost wingman” procedure to increase separation and reacquire contact. The flight demonstration included both a nominal formation flight component and an execution of the lost wingman scenario

Viking '75 spacecraft design and test summary. Volume 3: Engineering test summary

The engineering test program for the lander and the orbiter are presented. The engineering program was developed to achieve confidence that the design was adequate to survive the expected mission environments and to accomplish the mission objective

The aerodynamic challenges of the design and development of the space shuttle orbiter

The major aerodynamic design challenge at the beginning of the United States Space Transportation System (STS) research and development phase was to design a vehicle that would fly as a spacecraft during early entry and as an aircraft during the final phase of entry. The design was further complicated because the envisioned vehicle was statically unstable during a portion of the aircraft mode of operation. The second challenge was the development of preflight aerodynamic predictions with an accuracy consistent with conducting a manned flight on the initial orbital flight. A brief history of the early contractual studies is presented highlighting the technical results and management decisions influencing the aerodynamic challenges. The configuration evolution and the development of preflight aerodynamic predictions will be reviewed. The results from the first four test flights shows excellent agreement with the preflight aerodynamic predictions over the majority of the flight regimes. The only regimes showing significant disagreement is confined primarily to early entry, where prediction of the basic vehicle trim and the influence of the reaction control system jets on the flow field were found to be deficient. Postflight results are analyzed to explain these prediction deficiencies

The Structure of Differential Invariants and Differential Cut Elimination

The biggest challenge in hybrid systems verification is the handling of differential equations. Because computable closed-form solutions only exist for very simple differential equations, proof certificates have been proposed for more scalable verification. Search procedures for these proof certificates are still rather ad-hoc, though, because the problem structure is only understood poorly. We investigate differential invariants, which define an induction principle for differential equations and which can be checked for invariance along a differential equation just by using their differential structure, without having to solve them. We study the structural properties of differential invariants. To analyze trade-offs for proof search complexity, we identify more than a dozen relations between several classes of differential invariants and compare their deductive power. As our main results, we analyze the deductive power of differential cuts and the deductive power of differential invariants with auxiliary differential variables. We refute the differential cut elimination hypothesis and show that, unlike standard cuts, differential cuts are fundamental proof principles that strictly increase the deductive power. We also prove that the deductive power increases further when adding auxiliary differential variables to the dynamics

Workshop on Verification and Theorem Proving for Continuous Systems (NetCA Workshop 2005)

Oxford, UK, 26 August 200

Eulerian simulation of the fluid dynamics of helicopter brownout

A computational model is presented that can be used to simulate the development of the dust cloud that can be entrained into the air when a helicopter is operated close to the ground in desert or dusty conditions. The physics of this problem, and the associated pathological condition known as ‘brownout’ where the pilot loses situational awareness as a result of his vision being occluded by dust suspended in the flow around the helicopter, is acknowledged to be very complex. The approach advocated here involves an approximation to the full dynamics of the coupled particulate-air system. Away from the ground, the model assumes that the suspended particles remain in near equilibrium under the action of aerodynamic forces. Close to the ground, this model is replaced by an algebraic sublayer model for the saltation and entrainment process. The origin of the model in the statistical mechanics of a distribution of particles governed by aerodynamic forces allows the validity of the method to be evaluated in context by comparing the physical properties of the suspended particulates to the local properties of the flow field surrounding the helicopter. The model applies in the Eulerian frame of reference of most conventional Computational Fluid Dynamics codes and has been coupled with Brown’s Vorticity Transport Model. Verification of the predictions of the coupled model against experimental data for particulate entrainment and transport in the flow around a model rotor are encouraging. An application of the coupled model to analyzing the differences in the geometry and extent of the dust clouds that are produced by single main rotor and tandem-rotor configurations as they decelerate to land has shown that the location of the ground vortex and the size of any regions of recirculatory flow, should they exist, play a primary role in governing the extent of the dust cloud that is created by the helicopter

Development and Verification of a Flight Stack for a High-Altitude Glider in Ada/SPARK 2014

SPARK 2014 is a modern programming language and a new state-of-the-art tool set for development and verification of high-integrity software. In this paper, we explore the capabilities and limitations of its latest version in the context of building a flight stack for a high-altitude unmanned glider. Towards that, we deliberately applied static analysis early and continuously during implementation, to give verification the possibility to steer the software design. In this process we have identified several limitations and pitfalls of software design and verification in SPARK, for which we give workarounds and protective actions to avoid them. Finally, we give design recommendations that have proven effective for verification, and summarize our experiences with this new language