The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform
Roberto Sebastiani - One of the best experts on this subject based on the ideXlab platform.
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to Ackermann ize or not to Ackermann ize on efficiently handling uninterpreted function symbols in smt t
International Conference on Logic Programming, 2006Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto SebastianiAbstract: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.
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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, 2006Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto SebastianiAbstract: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.
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to Ackermann ize or not to Ackermann ize on efficiently handling uninterpreted function symbols in smt euf t
Lecture Notes in Computer Science, 2006Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto SebastianiAbstract: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.
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To Ackermann-ize or not to Ackermann-ize? on efficiently handling uninterpreted function symbols in SMT(EUF ∪ T)
Lecture Notes in Computer Science, 2006Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto SebastianiAbstract: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 - One of the best experts on this subject based on the ideXlab platform.
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a navigation architecture for Ackermann vehicles in precision farming
International Conference on Robotics and Automation, 2020Co-Authors: Renzo Fabrizio Carpio, Ciro Potena, Jacopo Maiolini, Giovanni Ulivi, Nicolás Bono Rosselló, Emanuele Garone, Andrea GasparriAbstract: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.
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A Navigation Architecture for Ackermann Vehicles in Precision Farming
IEEE Robotics and Automation Letters, 2020Co-Authors: Renzo Fabrizio Carpio, Ciro Potena, Jacopo Maiolini, Giovanni Ulivi, Nicolás Bono Rosselló, Emanuele Garone, Andrea GasparriAbstract: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 - One of the best experts on this subject based on the ideXlab platform.
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to Ackermann ize or not to Ackermann ize on efficiently handling uninterpreted function symbols in smt t
International Conference on Logic Programming, 2006Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto SebastianiAbstract: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.
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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, 2006Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto SebastianiAbstract: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.
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to Ackermann ize or not to Ackermann ize on efficiently handling uninterpreted function symbols in smt euf t
Lecture Notes in Computer Science, 2006Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto SebastianiAbstract: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.
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To Ackermann-ize or not to Ackermann-ize? on efficiently handling uninterpreted function symbols in SMT(EUF ∪ T)
Lecture Notes in Computer Science, 2006Co-Authors: Roberto Bruttomesso, Alessandro Cimatti, Anders Franzen, Alberto Griggio, Alessandro Santuari, Roberto SebastianiAbstract: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.
Jae Weon Choi - One of the best experts on this subject based on the ideXlab platform.
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Ackermann-like eigenvalue assignment formulae for linear time-varying systems
IEE Proceedings - Control Theory and Applications, 2005Co-Authors: Jae Weon ChoiAbstract:Eigenvalue assignment techniques for linear time-varying systems are presented as a way of achieving feedback stabilisation. For this, novel eigenvalue concepts, which are the time-varying counterparts of conventional (time-invariant) eigenvalue ideas, are introduced. Ackermann-like formulae for both SISO and MIMO linear time-varying systems are proposed. It is believed that these techniques are the generalised versions of the Ackermann formulae for linear time-invariant systems. The advantages of the proposed Ackermann-like formulae are that they neither require the transformation of the original system into a phase-variable form nor the computation of the eigenvalues of the original system, and they can allow the closed-loop system to have desired eigenvalue trajectories rather than fixed eigenvalue locations. Two examples are given to demonstrate the capabilities of the proposed techniques.
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Efficient eigenvalue assignment for linear time-varying systems
ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570), 2001Co-Authors: Jae Weon ChoiAbstract:This paper deals with the eigenvalue assignment for linear time-varying systems to achieve feedback stabilization. For this, we introduce the novel eigenvalue concepts. It is believed that this technique is the generalized version of the Ackerman formula for linear time-invariant systems. The advantages of the proposed Ackerman-like formula are that it does not require the transformation of the original system into the phase-variable form nor the computation of eigenvalues of the original system.
Renzo Fabrizio Carpio - One of the best experts on this subject based on the ideXlab platform.
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a navigation architecture for Ackermann vehicles in precision farming
International Conference on Robotics and Automation, 2020Co-Authors: Renzo Fabrizio Carpio, Ciro Potena, Jacopo Maiolini, Giovanni Ulivi, Nicolás Bono Rosselló, Emanuele Garone, Andrea GasparriAbstract: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.
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A Navigation Architecture for Ackermann Vehicles in Precision Farming
IEEE Robotics and Automation Letters, 2020Co-Authors: Renzo Fabrizio Carpio, Ciro Potena, Jacopo Maiolini, Giovanni Ulivi, Nicolás Bono Rosselló, Emanuele Garone, Andrea GasparriAbstract: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.
