The Experts below are selected from a list of 8241 Experts worldwide ranked by ideXlab platform
Paul Newman - One of the best experts on this subject based on the ideXlab platform.
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a method for protocol based collision avoidance between autonomous Marine surface craft
Journal of Field Robotics, 2006Co-Authors: Michael R. Benjamin, J. Curcio, John J Leonard, Paul NewmanAbstract:This paper is concerned with the in-field autonomous operation of unmanned Marine Vehicles in accordance with convention for safe and proper collision avoidance as prescribed by the Coast Guard Collision Regulations (COLREGS). These rules are written to train and guide safe human operation of Marine Vehicles and are heavily dependent on human common sense in determining rule applicability as well as rule execution, especially when multiple rules apply simultaneously. To capture, the flexibility exploited by humans, this work applies a novel method of multiobjective optimization, interval programming, in a behavior-based control framework for representing the navigation rules, as well as task behaviors, in a way that achieves simultaneous optimal satisfaction. We present experimental validation of this approach using multiple autonomous surface craft. This work represents the first in-field demonstration of multiobjective optimization applied to autonomous COLREGS-based Marine Vehicle navigation. © 2006 Wiley Periodicals, Inc.
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Multi-objective optimization of sensor quality with efficient Marine Vehicle task execution
Proceedings 2006 IEEE International Conference on Robotics and Automation 2006. ICRA 2006., 2006Co-Authors: M. Benjamin, Martin Grund, Paul NewmanAbstract:This paper describes the in-field operation of two interacting autonomous Marine Vehicles to demonstrate the suitability of interval programming (IvP), a novel mathematical model for multiple-objective optimization. Broadly speaking, IvP coordinates competing control needs such as primary task execution that depends on a sufficient position estimate, and Vehicle maneuvers that will improve that position estimate. In this work, Vehicles cooperate to improve their position estimates using a sequence of Vehicle-to-Vehicle range estimates from acoustic modems. Coordinating primary task execution and sensor quality maintenance is a ubiquitous problem, especially in underwater Marine Vehicles. This work represents the first use of multiobjective optimization in a behavior-based architecture to address this problem
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ICRA - Navigation of unmanned Marine Vehicles in accordance with the rules of the road
Proceedings 2006 IEEE International Conference on Robotics and Automation 2006. ICRA 2006., 2006Co-Authors: Michael R. Benjamin, J. Curcio, John J Leonard, Paul NewmanAbstract:This paper is concerned with the in-field autonomous operation of unmanned Marine Vehicles in accordance with convention for safe and proper collision avoidance as prescribed by the coast guard collision regulations (COLREGS). These rules are written to train and guide safe human operation of Marine Vehicles and are heavily dependent on human common sense in determining rule applicability as well as rule execution, especially when multiple rules apply simultaneously. To capture the flexibility exploited by humans, this work applies a novel method of multi-objective optimization, interval programming, in a behavior-based control framework for representing the navigation rules, as well as task behaviors, in a way that achieves simultaneous optimal satisfaction. We present experimental validation of this approach using multiple autonomous surface craft. This work represents the first in-field demonstration of multiobjective optimization applied to autonomous COLREGS-based Marine Vehicle navigation
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ICRA - Multi-objective optimization of sensor quality with efficient Marine Vehicle task execution
Proceedings 2006 IEEE International Conference on Robotics and Automation 2006. ICRA 2006., 1Co-Authors: Michael R. Benjamin, Martin Grund, Paul NewmanAbstract:This paper describes the in-field operation of two interacting autonomous Marine Vehicles to demonstrate the suitability of interval programming (IvP), a novel mathematical model for multiple-objective optimization. Broadly speaking, IvP coordinates competing control needs such as primary task execution that depends on a sufficient position estimate, and Vehicle maneuvers that will improve that position estimate. In this work, Vehicles cooperate to improve their position estimates using a sequence of Vehicle-to-Vehicle range estimates from acoustic modems. Coordinating primary task execution and sensor quality maintenance is a ubiquitous problem, especially in underwater Marine Vehicles. This work represents the first use of multiobjective optimization in a behavior-based architecture to address this problem
Michael R. Benjamin - One of the best experts on this subject based on the ideXlab platform.
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a method for protocol based collision avoidance between autonomous Marine surface craft
Journal of Field Robotics, 2006Co-Authors: Michael R. Benjamin, J. Curcio, John J Leonard, Paul NewmanAbstract:This paper is concerned with the in-field autonomous operation of unmanned Marine Vehicles in accordance with convention for safe and proper collision avoidance as prescribed by the Coast Guard Collision Regulations (COLREGS). These rules are written to train and guide safe human operation of Marine Vehicles and are heavily dependent on human common sense in determining rule applicability as well as rule execution, especially when multiple rules apply simultaneously. To capture, the flexibility exploited by humans, this work applies a novel method of multiobjective optimization, interval programming, in a behavior-based control framework for representing the navigation rules, as well as task behaviors, in a way that achieves simultaneous optimal satisfaction. We present experimental validation of this approach using multiple autonomous surface craft. This work represents the first in-field demonstration of multiobjective optimization applied to autonomous COLREGS-based Marine Vehicle navigation. © 2006 Wiley Periodicals, Inc.
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ICRA - Navigation of unmanned Marine Vehicles in accordance with the rules of the road
Proceedings 2006 IEEE International Conference on Robotics and Automation 2006. ICRA 2006., 2006Co-Authors: Michael R. Benjamin, J. Curcio, John J Leonard, Paul NewmanAbstract:This paper is concerned with the in-field autonomous operation of unmanned Marine Vehicles in accordance with convention for safe and proper collision avoidance as prescribed by the coast guard collision regulations (COLREGS). These rules are written to train and guide safe human operation of Marine Vehicles and are heavily dependent on human common sense in determining rule applicability as well as rule execution, especially when multiple rules apply simultaneously. To capture the flexibility exploited by humans, this work applies a novel method of multi-objective optimization, interval programming, in a behavior-based control framework for representing the navigation rules, as well as task behaviors, in a way that achieves simultaneous optimal satisfaction. We present experimental validation of this approach using multiple autonomous surface craft. This work represents the first in-field demonstration of multiobjective optimization applied to autonomous COLREGS-based Marine Vehicle navigation
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COLREGS-based navigation of autonomous Marine Vehicles
2004 IEEE OES Autonomous Underwater Vehicles (IEEE Cat. No.04CH37578), 2004Co-Authors: Michael R. Benjamin, J. CurcioAbstract:This paper addresses the issue of autonomous control and safe navigation in an unmanned Marine Vehicle. Primarily it is concerned with the issue of effective collision avoidance. The first part of the paper examines known legal issues regarding autonomous Marine Vehicles, and the second part addresses how to provide an autonomous COLREGS capability in an autonomous Marine Vehicle.
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ICRA - Multi-objective optimization of sensor quality with efficient Marine Vehicle task execution
Proceedings 2006 IEEE International Conference on Robotics and Automation 2006. ICRA 2006., 1Co-Authors: Michael R. Benjamin, Martin Grund, Paul NewmanAbstract:This paper describes the in-field operation of two interacting autonomous Marine Vehicles to demonstrate the suitability of interval programming (IvP), a novel mathematical model for multiple-objective optimization. Broadly speaking, IvP coordinates competing control needs such as primary task execution that depends on a sufficient position estimate, and Vehicle maneuvers that will improve that position estimate. In this work, Vehicles cooperate to improve their position estimates using a sequence of Vehicle-to-Vehicle range estimates from acoustic modems. Coordinating primary task execution and sensor quality maintenance is a ubiquitous problem, especially in underwater Marine Vehicles. This work represents the first use of multiobjective optimization in a behavior-based architecture to address this problem
Peter Pd Dr.-ing. Habil. Otto - One of the best experts on this subject based on the ideXlab platform.
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Cooperative line of sight target tracking for heterogeneous unmanned Marine Vehicle teams
Robotics and Autonomous Systems, 2015Co-Authors: Thomas Glotzbach, Matthias Dipl.-ing. Schneider, Peter Pd Dr.-ing. Habil. OttoAbstract:In this paper we present the principle of Cooperative Line Of Sight Target Tracking (CLOSTT) for Heterogeneous Unmanned Marine Vehicle Teams. Thereby CLOSTT is part of a control architecture developed to coordinate existing single heterogeneous autonomous Marine Vehicles as a team. Within this control architecture CLOSTT separately offers a solution to the task of following a moving underwater target with a team of unmanned Marine Vehicles. We describe an algorithm for target tracking by a team of autonomous Marine Vehicles.A general control architecture for such a team is described.Focus is put on tracking an underwater target by a team of autonomous Marine Vehicles.The tracking algorithm was validated in real sea trials.In the trials, an acoustic communication link was in the loop.
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Obstacle avoidance for Multiple Unmanned Marine Vehicles (MUMVs) in close formation
OCEANS 2009-EUROPE, 2009Co-Authors: Thomas Glotzbach, Matthias Dipl.-ing. Schneider, Marco Jacobi, Peter Pd Dr.-ing. Habil. OttoAbstract:In this paper we demonstrate a method for obstacle avoidance of heterogeneous unmanned Marine Vehicle teams. The task is to find a collision free path for a Vehicle group moving in close formation through an area with known obstacles, while keeping formation when possible and change formation when necessary. Whenever possible, they shall use their original paths in desired formation, as only this performance will bring benefit (e.g. collecting data where the measurements of several Vehicles shall be merged at the end).1
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Path Planning for Cooperative Line Of Sight Target Tracking of Heterogeneous Unmanned Marine Vehicle Teams
IFAC Proceedings Volumes, 2009Co-Authors: Thomas Glotzbach, Matthias Dipl.-ing. Schneider, Peter Pd Dr.-ing. Habil. OttoAbstract:Abstract In this paper we suggest a procedure to perform path planning for cooperative target pursuit, performed by a heterogeneous team of unmanned Marine Vehicles. This work was performed in the framework of the research project GREX (IST-Project-No. 035223) which aims for the realization of several mission scenarios including cooperative Marine Vehicles. We will describe the algorithms for the team leader to calculate new paths for all team members online and demonstrate the results in a computer simulation.
Martin Grund - One of the best experts on this subject based on the ideXlab platform.
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Multi-objective optimization of sensor quality with efficient Marine Vehicle task execution
Proceedings 2006 IEEE International Conference on Robotics and Automation 2006. ICRA 2006., 2006Co-Authors: M. Benjamin, Martin Grund, Paul NewmanAbstract:This paper describes the in-field operation of two interacting autonomous Marine Vehicles to demonstrate the suitability of interval programming (IvP), a novel mathematical model for multiple-objective optimization. Broadly speaking, IvP coordinates competing control needs such as primary task execution that depends on a sufficient position estimate, and Vehicle maneuvers that will improve that position estimate. In this work, Vehicles cooperate to improve their position estimates using a sequence of Vehicle-to-Vehicle range estimates from acoustic modems. Coordinating primary task execution and sensor quality maintenance is a ubiquitous problem, especially in underwater Marine Vehicles. This work represents the first use of multiobjective optimization in a behavior-based architecture to address this problem
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ICRA - Multi-objective optimization of sensor quality with efficient Marine Vehicle task execution
Proceedings 2006 IEEE International Conference on Robotics and Automation 2006. ICRA 2006., 1Co-Authors: Michael R. Benjamin, Martin Grund, Paul NewmanAbstract:This paper describes the in-field operation of two interacting autonomous Marine Vehicles to demonstrate the suitability of interval programming (IvP), a novel mathematical model for multiple-objective optimization. Broadly speaking, IvP coordinates competing control needs such as primary task execution that depends on a sufficient position estimate, and Vehicle maneuvers that will improve that position estimate. In this work, Vehicles cooperate to improve their position estimates using a sequence of Vehicle-to-Vehicle range estimates from acoustic modems. Coordinating primary task execution and sensor quality maintenance is a ubiquitous problem, especially in underwater Marine Vehicles. This work represents the first use of multiobjective optimization in a behavior-based architecture to address this problem
Thomas Glotzbach - One of the best experts on this subject based on the ideXlab platform.
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Cooperative line of sight target tracking for heterogeneous unmanned Marine Vehicle teams
Robotics and Autonomous Systems, 2015Co-Authors: Thomas Glotzbach, Matthias Dipl.-ing. Schneider, Peter Pd Dr.-ing. Habil. OttoAbstract:In this paper we present the principle of Cooperative Line Of Sight Target Tracking (CLOSTT) for Heterogeneous Unmanned Marine Vehicle Teams. Thereby CLOSTT is part of a control architecture developed to coordinate existing single heterogeneous autonomous Marine Vehicles as a team. Within this control architecture CLOSTT separately offers a solution to the task of following a moving underwater target with a team of unmanned Marine Vehicles. We describe an algorithm for target tracking by a team of autonomous Marine Vehicles.A general control architecture for such a team is described.Focus is put on tracking an underwater target by a team of autonomous Marine Vehicles.The tracking algorithm was validated in real sea trials.In the trials, an acoustic communication link was in the loop.
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Obstacle avoidance for Multiple Unmanned Marine Vehicles (MUMVs) in close formation
OCEANS 2009-EUROPE, 2009Co-Authors: Thomas Glotzbach, Matthias Dipl.-ing. Schneider, Marco Jacobi, Peter Pd Dr.-ing. Habil. OttoAbstract:In this paper we demonstrate a method for obstacle avoidance of heterogeneous unmanned Marine Vehicle teams. The task is to find a collision free path for a Vehicle group moving in close formation through an area with known obstacles, while keeping formation when possible and change formation when necessary. Whenever possible, they shall use their original paths in desired formation, as only this performance will bring benefit (e.g. collecting data where the measurements of several Vehicles shall be merged at the end).1
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Path Planning for Cooperative Line Of Sight Target Tracking of Heterogeneous Unmanned Marine Vehicle Teams
IFAC Proceedings Volumes, 2009Co-Authors: Thomas Glotzbach, Matthias Dipl.-ing. Schneider, Peter Pd Dr.-ing. Habil. OttoAbstract:Abstract In this paper we suggest a procedure to perform path planning for cooperative target pursuit, performed by a heterogeneous team of unmanned Marine Vehicles. This work was performed in the framework of the research project GREX (IST-Project-No. 035223) which aims for the realization of several mission scenarios including cooperative Marine Vehicles. We will describe the algorithms for the team leader to calculate new paths for all team members online and demonstrate the results in a computer simulation.