Pappas, George J

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Now showing 1 - 10 of 121
  • Publication
    Abstractions of Constrained Linear Systems
    (2003-06-04) Tanner, Herbert G; Pappas, George J
    Simulation relations are powerful abstraction techniques in computer science that reduce the complexity of analysis and design of labeled transition systems. In this paper, we define and characterize simulation relations for discrete-time linear systems in the presence of state and input constraints. Given a discrete-time linear system and the associated constraints, we consider a control-abstract embedding into a transition system. We then establish necessary and sufficient conditions for one constrained linear system to simulate the transitions of the other. Checking the simulation conditions is formulated as a linear programming problem which can be efficiently solved for systems of large dimensions. We provide an example where our approach is applied to the hybrid model of the Electronic Throttle Control (ETC) System.
  • Publication
    Cooperative Air and Ground Survaillance
    (2006-09-01) Grocholsky, Ben; Kumar, Vijay; Keller, James; Pappas, George J
    Unmanned aerial vehicles (UAVs) can be used to cover large areas searching for targets. However, sensors on UAVs are typically limited in their accuracy of localization of targets on the ground. On the other hand, unmanned ground vehicles (UGVs) can be deployed to accurately locate ground targets, but they have the disadvantage of not being able to move rapidly or see through such obstacles as buildings or fences. In this article, we describe how we can exploit this synergy by creating a seamless network of UAVs and UGVs. The keys to this are our framework and algorithms for search and localization, which are easily scalable to large numbers of UAVs and UGVs and are transparent to the specificity of individual platforms. We describe our experimental testbed, the framework and algorithms, and some results.
  • Publication
    Estimation of Blood Oxygen Content Using Context-Aware Filtering
    (2016-04-01) Ivanov, Radoslav; Atanasov, Nikolay; Weimer, James; Simpao, Allan F; Rehman, Mohamed A; Pappas, George; Lee, Insup; Pajic, Miroslav
    In this paper we address the problem of estimating the blood oxygen concentration in children during surgery.Currently, the oxygen content can only be measured through invasive means such as drawing blood from the patient. In this work, we attempt to perform estimation by only using other non-invasive measurements (e.g., fraction of oxygen in inspired air, volume of inspired air) collected during surgery. Although models mapping these measurements to blood oxygen content contain multiple parameters that vary widely across patients, the non-invasive measurements can be used to provide binary information about whether the oxygen concentration is rising or dropping. This information can then be incorporated in a context-aware filter that is used to combine regular continuous measurements with discrete detection events in order to improve estimation. We evaluate the filter using real-patient data collected over the last decade at the Children’s Hospital of Philadelphia and show that it is a promising approach for the estimation of unobservable physiological variables.
  • Publication
    Synergies in Feature Localization by Air-Ground Robot Teams
    (2004-06-18) Kumar, R. Vijay; Grocholsky, Ben; Taylor, Camillo J; Bayraktar, Selcuk; Pappas, George J
    This paper describes the implementation of a decentralized architecture for autonomous teams of aerial and ground vehicles engaged in active perception. We provide a theoretical framework based on an established approach to the underlying sensor fusion problem [3]. This provides transparent integration of information from heterogeneous sources. The approach is extended to include an information-theoretic utility measure that captures the task objective and robot inter-dependencies. A distributed solution mechanism is employed to determine information maximizing trajectories and assignments subject to the constraints of individual vehicle and sensor sub-systems. This architecture enables the benefit of the complementary aerial and ground based vehicle and sensor capabilities to be realized. The approach is applied to missions involving searching for and tracking multiple ground targets. Experimental results for vehicles equipped with cameras are presented. These illustrate the impact of the team configuration on overall system performance.
  • Publication
    Modeling and Analyzing Biomolecular Networks
    (2002-01-01) Alur, Rajeev; Kumar, R. Vijay; Mintz, Max L; Pappas, George J; Belta, Calin; Rubin, Harvey; Schug, Jonathan
    The authors argue for the need to model and analyze biological networks at molecular and cellular levels. They propose a computational toolbox for biologists. Central to their approach is the paradigm of hybrid models in which discrete events are combined with continuous differential equations to capture switching behavior.
  • Publication
    Attack-Resilient State Estimation in the Presence of Noise
    (2015-12-01) Pajic, Miroslav; Lee, Insup; Tabuada, Paulo; Pappas, George
    We consider the problem of attack-resilient state estimation in the presence of noise. We focus on the most general model for sensor attacks where any signal can be injected via the compromised sensors. An l0-based state estimator that can be formulated as a mixed-integer linear program and its convex relaxation based on the l1 norm are presented. For both l0 and l1-based state estimators, we derive rigorous analytic bounds on the state-estimation errors. We show that the worst-case error is linear with the size of the noise, meaning that the attacker cannot exploit noise and modeling errors to introduce unbounded state-estimation errors. Finally, we show how the presented attack-resilient state estimators can be used for sound attack detection and identification, and provide conditions on the size of attack vectors that will ensure correct identification of compromised sensors.
  • Publication
    Approximate Bisimulations for Nonlinear Dynamical Systems
    (2005-12-12) Girard, Antoine; Pappas, George J
    The notion of exact bisimulation equivalence for nondeterministic discrete systems has recently resulted in notions of exact bisimulation equivalence for continuous and hybrid systems. In this paper, we establish the more robust notion of approximate bisimulation equivalence for nondeterministic nonlinear systems. This is achieved by requiring that a distance between system observations starts and remains, close, in the presence of nondeterministic system evolution. We show that approximate bisimulation relations can be characterized using a class of functions called bisimulation functions. For nondeterministic nonlinear systems, we show that conditions for the existence of bisimulation functions can be expressed in terms of Lyapunov-like inequalities, which for deterministic systems can be computed using recent sum-of-squares techniques. Our framework is illustrated on a safety verification example.
  • Publication
    Elastic Multi-Particle Systems for Bounded-Curvature Path Planning
    (2008-06-11) Ahmadzadeh, Ali; Jadbabaie, Ali; Pappas, George J; Kumar, Vijay
    This paper investigates a path planning algorithm for Dubins vehicles. Our approach is based on approximation of the trajectories of vehicles using sequence of waypoints and treating each way point as a moving particle in the space. We define interaction forces between the particles such that the resulting multi-particle system will be stable, moreover, the trajectories generated by the waypoints in the equilibria of the multi-particle system will satisfy all of the hard constraint such as bounded-curvature constraint and obstacle avoidance.
  • Publication
    Abstractions of Hamiltonian Control Systems
    (2001-12-04) Tabuada, Paulo; Pappas, George J
    Given a control system and a desired property, an abstracted system is a reduced system that preserves the property of interest while ignoring modeling detail. In previous work, we considered abstractions of linear and nonlinear analytic control systems while preserving reachability properties. In this paper we consider the abstraction problem for Hamiltonian control systems, that is, we preserve the Hamiltonian structure during the abstraction process. We show how the mechanical structure of Hamiltonian control systems can be exploited to simplify the abstraction computations and we provide conditions under which the local accessibility properties of the abstracted Hamiltonian system are equivalent to the local accessibility properties of the original Hamiltonian control system.
  • Publication
    Genetic network identification using convex programming
    (2009-05-19) Zavlanos, Michael; Julius, A; Pappas, George J; Boyd, S

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