Planning Random path distributions for ambush games in unstructured environments

Operating vehicles in adversarial environments require non-conventional planning techniques. A two-player, zero-sum non-cooperative game is introduced, which is solved via a linear program. An extension is proposed to construct networks displaying good representations of the environment characteristics, while offering acceptable results for the technique used. Sensitivity of the solution to the LP solver algorithm is identified. The performances of the planner are finally assessed by comparison with those of conventional planners. Results are used to formulate secondary objectives to the problem

Automated, Credible Autocoding of An Unmanned Aggressive Maneuvering Car Controller

This article describes the application of a credible autocoding framework for control systems towards a nonlinear car controller example. The framework generates code, along with guarantees of high level functional properties about the code that can be independently verified. These high-level functional properties not only serves as a certificate of good system behvaior but also can be used to guarantee the absence of runtime errors. In one of our previous works, we have constructed a prototype autocoder with proofs that demonstrates this framework in a fully automatic fashion for linear and quasi-nonlinear controllers. With the nonlinear car example, we propose to further extend the prototype's dataflow annotation language environment with with several new annotation symbols to enable the expression of general predicates and dynamical systems. We demonstrate manually how the new extensions to the prototype autocoder work on the car controller using the output language Matlab. Finally, we discuss the requirements and scalability issues of the automatic analysis and verification of the documented output code

Control software analysis, part II: Closed-loop analysis

The analysis and proper documentation of the properties of closed-loop control software presents many distinct aspects from the analysis of the same software running open-loop. Issues of physical system representations arise, and it is desired that such representations remain independent from the representations of the control program. For that purpose, a concurrent program representation of the plant and the control processes is proposed, although the closed-loop system is sufficiently serialized to enable a sequential analysis. While dealing with closed-loop system properties, it is also shown by means of examples how special treatment of nonlinearities extends from the analysis of control specifications to code analysis.Comment: 16 pages, 2 figure

Control software analysis, Part I Open-loop properties

As the digital world enters further into everyday life, questions are raised about the increasing challenges brought by the interaction of real-time software with physical devices. Many accidents and incidents encountered in areas as diverse as medical systems, transportation systems or weapon systems are ultimately attributed to "software failures". Since real-time software that interacts with physical systems might as well be called control software, the long litany of accidents due to real-time software failures might be taken as an equally long list of opportunities for control systems engineering. In this paper, we are interested only in run-time errors in those pieces of software that are a direct implementation of control system specifications: For well-defined and well-understood control architectures such as those present in standard textbooks on digital control systems, the current state of theoretical computer science is well-equipped enough to address and analyze control algorithms. It appears that a central element to these analyses is Lyapunov stability theory, which translate into invariant theory in computer implementations.Comment: 20 pages, 3 figure

Experiments with small helicopter automated landings at unusual attitudes

This paper describes a set of experiments involving small helicopters landing automated landing at unusual attitudes. By leveraging the increased agility of small air vehicles, we show that it is possible to automatically land a small helicopter on surfaces pitched at angles up to 60 degrees. Such maneuvers require considerable agility from the vehicle and its avionics system, and they pose significant technical and safety challenges. Our work builds upon previous activities in human-inspired, high-agility flight for small rotorcraft. However, it was not possible to leverage manual flight test data to extract landing maneuvers due to stringent attitude and position control requirements. Availability of low-cost, local navigation systems requiring no on-board instrumentation has proven particularly important for these experiments to be successful.Comment: 20 page

Structural price model for electricity coupled markets

We propose a new structural model that can compute the electricity spot and forward prices in two coupled markets with limited interconnection and multiple fuels. We choose a structural approach in order to represent some key characteristics of electricity spot prices such as their link to fuel prices, consumption level and production fleet. With this model, explicit formulas are also available for forward prices and other derivatives. We give some illustrative results of the behaviour of spot and forward prices, and of the values of transmission rights

Environmental benefits of enhanced surveillance technology on airport departure operations

Airport departure operations constitute an important source of airline delays and passenger frustration. Excessive surface traffic is the cause of increased controller and pilot workload; It is also the source of increased emissions; It worsens traffic safety and often does not yield improved runway throughput. Acknowledging this fact, this paper explores some of the feedback mechanisms by which airport traffic can be optimized in real time according to its current degree of congestion. In particular, it examines the environmnetal benefits that improved surveillance technologies can bring in the context of gate- or spot-release aircraft strategies. It is shown that improvements can lead yield 4% to 6% emission reductions for busy airports like New-York La Guardia or Seattle Tacoma. These benefits come on top of the benefits already obtained by adopting threshold strategies currently under evaluation.Comment: 25 pages, submitted to US/EUrope 2011 ATM semina

A Bayesian approach to change point analysis of discrete time series

In this work we consider time series with a finite number of discrete point changes. We assume that the data in each segment follows a different probability density functions (pdf). We focus on the case where the data in all segments are modeled by Gaussian probability density functions with different means, variances and correlation lengths. We put a prior law on the change point instances (Poisson process) as well as on these different parameters(conjugate priors) and give the expression of the posterior probality distributions of these change points. The computations are done by using an appropriate Markov Chain Monte Carlo (MCMC) technique. The problem as we stated can also be considered as an unsupervised classification and/or segmentation of the time serie. This analogy gives us the possibility to propose alternative modeling and computation of change points, which are more appropriate for multivariate signals, for example in image processing

A Hidden Markov model for Bayesian data fusion of multivariate signals

In this work we propose a Bayesian framework for data fusion of multivariate signals which arises in imaging systems. More specifically, we consider the case where we have observed two images of the same object through two different imaging processes. The objective of this work is then to propose a coherent approach to combine these data sets to obtain a segmented image which can be considered as the fusion result of these two images. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently, with common hidden classification label variables which is modeled by the Potts Markov Random Field. We propose then an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results and applications.Comment: presented at Fifth Int. Triennial Calcutta Symposium on Probability and Statistics, 28-31 December. 2003, Dept. of Statistics, Calcutta University, Kolkata, Indi

A hidden Markov Model for image fusion and their joint segmentation in medical image computing

In this work we propose a Bayesian framework for fully automated image fusion and their joint segmentation. More specifically, we consider the case where we have observed images of the same object through different image processes or through different spectral bands. The objective of this work is then to propose a coherent approach to combine these data sets and obtain a segmented image which can be considered as the fusion result of these observations. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently, with common hidden classification label variables which are modeled by the Potts Markov Random Field. We propose an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results and applications.Comment: submitted to MICCAI, St. Malo, Franc