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Ackermann

The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform

Roberto Sebastiani – 1st expert on this subject based on the ideXlab platform

  • to Ackermann ize or not to Ackermann ize on efficiently handling uninterpreted function symbols in smt t
    International Conference on Logic Programming, 2006
    Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto Sebastiani

    Abstract:

    Satisfiability Modulo Theories is the problem of deciding the satisfiability of a formula with respect to a given background theory . When is the combination of two simpler theories and , a standard and general approach is to handle the integration of and by performing some form of search on the equalities between the shared variables.

    A frequent and very relevant sub-case of is when is the theory of Equality and Uninterpreted Functions . For this case, an alternative approach is to eliminate first all uninterpreted function symbols by means of Ackermann‘s expansion, and then to solve the resulting problem.

    In this paper we build on the empirical observation that there is no absolute winner between these two alternative approaches, and that the performance gaps between them are often dramatic, in either direction.

    We propose a simple technique for estimating a priori the costs and benefits, in terms of the size of the search space of an tool, of applying Ackermann‘s expansion to all or part of the function symbols.

    A thorough experimental analysis, including the benchmarks of the SMT’05 competition, shows that the proposed technique is extremely effective in improving the overall performance of the tool.

  • LPAR – To Ackermann-ize or not to Ackermann-ize? on efficiently handling uninterpreted function symbols in SMT ( ∪T )
    Logic for Programming Artificial Intelligence and Reasoning, 2006
    Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto Sebastiani

    Abstract:

    Satisfiability Modulo Theories is the problem of deciding the satisfiability of a formula with respect to a given background theory . When is the combination of two simpler theories and , a standard and general approach is to handle the integration of and by performing some form of search on the equalities between the shared variables.

    A frequent and very relevant sub-case of is when is the theory of Equality and Uninterpreted Functions . For this case, an alternative approach is to eliminate first all uninterpreted function symbols by means of Ackermann‘s expansion, and then to solve the resulting problem.

    In this paper we build on the empirical observation that there is no absolute winner between these two alternative approaches, and that the performance gaps between them are often dramatic, in either direction.

    We propose a simple technique for estimating a priori the costs and benefits, in terms of the size of the search space of an tool, of applying Ackermann‘s expansion to all or part of the function symbols.

    A thorough experimental analysis, including the benchmarks of the SMT’05 competition, shows that the proposed technique is extremely effective in improving the overall performance of the tool.

  • to Ackermann ize or not to Ackermann ize on efficiently handling uninterpreted function symbols in smt euf t
    Lecture Notes in Computer Science, 2006
    Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto Sebastiani

    Abstract:

    Satisfiability Modulo Theories (SMT(T)) is the problem of deciding the satisfiability of a formula with respect to a given background theory T. When T is the combination of two simpler theories T 1 and T 2 . (SMT(T 1 ∪ T 2 )), a standard and general approach is to handle the integration of T 1 and T 2 by performing some form of search on the equalities between the shared variables. A frequent and very relevant sub-case of SMT(T 1 ∪ T 2 ) is when T 1 is the theory of Equality and Uninterpreted Functions (EUF). For this case, an alternative approach is to eliminate first all uninterpreted function symbols by means of Ackermann‘s expansion, and then to solve the resulting SMT (T 2 ) problem. In this paper we build on the empirical observation that there is no absolute winner between these two alternative approaches, and that the performance gaps between them are often dramatic, in either direction. We propose a simple technique for estimating a priori the costs and benefits, in terms of the size of the search space of an SMT tool, of applying Ackermann‘s expansion to all or part of the function symbols. A thorough experimental analysis, including the benchmarks of the SMT’05 competition, shows that the proposed technique is extremely effective in improving the overall performance of the SMT tool.

Andrea Gasparri – 2nd expert on this subject based on the ideXlab platform

  • a navigation architecture for Ackermann vehicles in precision farming
    International Conference on Robotics and Automation, 2020
    Co-Authors: Renzo Fabrizio Carpio, Ciro Potena, Jacopo Maiolini, Giovanni Ulivi, Nicolás Bono Rosselló, Emanuele Garone, Andrea Gasparri

    Abstract:

    In this letter, inspired by the needs of the European H2020 Project PANTHEON, 1 1 [Online]. Available: https://www.project-pantheon.eu . we propose a full navigation stack purposely designed for the autonomous navigation of Ackermann steering vehicles in precision farming settings. The proposed stack is composed of a local planner and a pose regulation controller, both implemented in ROS. The local planner generates, in real-time, optimal trajectories described by a sequence of successive poses. The planning problem is formulated as a real-time cost-function minimization problem over a finite time horizon where the Ackermann kinematics and the presence of obstacles are encoded as constraints. The control law ensures the convergence toward each of these poses. To do so, in this letter we propose a novel non-smooth control law designed to ensure the solvability of the pose regulation problem for the Ackermann vehicle. Theoretical characterization of the convergence property of the proposed pose regulation controller is provided. Numerical simulations along with real-world experiments are provided to corroborate the effectiveness of the proposed navigation strategy.

  • A Navigation Architecture for Ackermann Vehicles in Precision Farming
    IEEE Robotics and Automation Letters, 2020
    Co-Authors: Renzo Fabrizio Carpio, Ciro Potena, Jacopo Maiolini, Giovanni Ulivi, Nicolás Bono Rosselló, Emanuele Garone, Andrea Gasparri

    Abstract:

    In this letter, inspired by the needs of the European H2020 Project PANTHEON1, we propose a full navigation stack purposely designed for the autonomous navigation of Ackermann steering vehicles in precision farming settings. The proposed stack is composed of a local planner and a pose regulation controller, both implemented in ROS. The local planner generates, in real-time, optimal trajectories described by a sequence of successive poses. The planning problem is formulated as a real-time cost-function minimization problem over a finite time horizon where the Ackermann kinematics and the presence of obstacles are encoded as constraints. The control law ensures the convergence toward each of these poses. To do so, in this letter we propose a novel non-smooth control law designed to ensure the solvability of the pose regulation problem for the Ackermann vehicle. Theoretical characterization of the convergence property of the proposed pose regulation controller is provided. Numerical simulations along with real-world experiments are provided to corroborate the effectiveness of the proposed navigation strategy.

Roberto Bruttomesso – 3rd expert on this subject based on the ideXlab platform

  • to Ackermann ize or not to Ackermann ize on efficiently handling uninterpreted function symbols in smt t
    International Conference on Logic Programming, 2006
    Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto Sebastiani

    Abstract:

    Satisfiability Modulo Theories is the problem of deciding the satisfiability of a formula with respect to a given background theory . When is the combination of two simpler theories and , a standard and general approach is to handle the integration of and by performing some form of search on the equalities between the shared variables.

    A frequent and very relevant sub-case of is when is the theory of Equality and Uninterpreted Functions . For this case, an alternative approach is to eliminate first all uninterpreted function symbols by means of Ackermann‘s expansion, and then to solve the resulting problem.

    In this paper we build on the empirical observation that there is no absolute winner between these two alternative approaches, and that the performance gaps between them are often dramatic, in either direction.

    We propose a simple technique for estimating a priori the costs and benefits, in terms of the size of the search space of an tool, of applying Ackermann‘s expansion to all or part of the function symbols.

    A thorough experimental analysis, including the benchmarks of the SMT’05 competition, shows that the proposed technique is extremely effective in improving the overall performance of the tool.

  • LPAR – To Ackermann-ize or not to Ackermann-ize? on efficiently handling uninterpreted function symbols in SMT ( ∪T )
    Logic for Programming Artificial Intelligence and Reasoning, 2006
    Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto Sebastiani

    Abstract:

    Satisfiability Modulo Theories is the problem of deciding the satisfiability of a formula with respect to a given background theory . When is the combination of two simpler theories and , a standard and general approach is to handle the integration of and by performing some form of search on the equalities between the shared variables.

    A frequent and very relevant sub-case of is when is the theory of Equality and Uninterpreted Functions . For this case, an alternative approach is to eliminate first all uninterpreted function symbols by means of Ackermann‘s expansion, and then to solve the resulting problem.

    In this paper we build on the empirical observation that there is no absolute winner between these two alternative approaches, and that the performance gaps between them are often dramatic, in either direction.

    We propose a simple technique for estimating a priori the costs and benefits, in terms of the size of the search space of an tool, of applying Ackermann‘s expansion to all or part of the function symbols.

    A thorough experimental analysis, including the benchmarks of the SMT’05 competition, shows that the proposed technique is extremely effective in improving the overall performance of the tool.

  • to Ackermann ize or not to Ackermann ize on efficiently handling uninterpreted function symbols in smt euf t
    Lecture Notes in Computer Science, 2006
    Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto Sebastiani

    Abstract:

    Satisfiability Modulo Theories (SMT(T)) is the problem of deciding the satisfiability of a formula with respect to a given background theory T. When T is the combination of two simpler theories T 1 and T 2 . (SMT(T 1 ∪ T 2 )), a standard and general approach is to handle the integration of T 1 and T 2 by performing some form of search on the equalities between the shared variables. A frequent and very relevant sub-case of SMT(T 1 ∪ T 2 ) is when T 1 is the theory of Equality and Uninterpreted Functions (EUF). For this case, an alternative approach is to eliminate first all uninterpreted function symbols by means of Ackermann‘s expansion, and then to solve the resulting SMT (T 2 ) problem. In this paper we build on the empirical observation that there is no absolute winner between these two alternative approaches, and that the performance gaps between them are often dramatic, in either direction. We propose a simple technique for estimating a priori the costs and benefits, in terms of the size of the search space of an SMT tool, of applying Ackermann‘s expansion to all or part of the function symbols. A thorough experimental analysis, including the benchmarks of the SMT’05 competition, shows that the proposed technique is extremely effective in improving the overall performance of the SMT tool.