The Experts below are selected from a list of 208002 Experts worldwide ranked by ideXlab platform
Chen Wang - One of the best experts on this subject based on the ideXlab platform.
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efficient algorithms for sensor deployment and routing in sensor networks for network Structured Environment monitoring
International Conference on Computer Communications, 2012Co-Authors: Shuguang Xiong, Haiying Shen, Chen WangAbstract:When monitoring Environments with wireless sensor networks, optimal sensor deployment is a fundamental issue and an effective means to achieve desired performance. Selecting best sensor deployment has a dependence on the deployment Environments. Existing works address sensor deployment within three types of Environments including one dimensional line, 2-D field and 3-D space. However, in many applications the deployment Environments usually have network structures, which cannot be simply classified as the three types. The deployed locations and communications of sensor nodes are limited onto the network edges, which make the deployment problem distinct from that in other types of Environments. In this paper, we study sensor deployment in network-Structured Environments and aim to achieve k-coverage while minimizing the number of sensor nodes. Furthermore, we jointly consider the optimization of sink deployment and routing strategies with the goal to minimize the network communication cost of data collection. To the best of our knowledge, this paper is the first one to tackle sensor/sink deployment under the deployment constraints imposed by the network structure. The hardness of the problems is shown. Polynomial-time algorithms are proposed to determine optimal sensor/sink deployment and routing strategies in tree-topology network structure. Efficient approximation algorithms are proposed for the general graph network structure and their performances are analyzed. Theoretical results and extensive simulations show the efficiency of the proposed algorithms.
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INFOCOM - Efficient algorithms for sensor deployment and routing in sensor networks for network-Structured Environment monitoring
2012 Proceedings IEEE INFOCOM, 2012Co-Authors: Shuguang Xiong, Haiying Shen, Chen WangAbstract:When monitoring Environments with wireless sensor networks, optimal sensor deployment is a fundamental issue and an effective means to achieve desired performance. Selecting best sensor deployment has a dependence on the deployment Environments. Existing works address sensor deployment within three types of Environments including one dimensional line, 2-D field and 3-D space. However, in many applications the deployment Environments usually have network structures, which cannot be simply classified as the three types. The deployed locations and communications of sensor nodes are limited onto the network edges, which make the deployment problem distinct from that in other types of Environments. In this paper, we study sensor deployment in network-Structured Environments and aim to achieve k-coverage while minimizing the number of sensor nodes. Furthermore, we jointly consider the optimization of sink deployment and routing strategies with the goal to minimize the network communication cost of data collection. To the best of our knowledge, this paper is the first one to tackle sensor/sink deployment under the deployment constraints imposed by the network structure. The hardness of the problems is shown. Polynomial-time algorithms are proposed to determine optimal sensor/sink deployment and routing strategies in tree-topology network structure. Efficient approximation algorithms are proposed for the general graph network structure and their performances are analyzed. Theoretical results and extensive simulations show the efficiency of the proposed algorithms.
E Badreddin - One of the best experts on this subject based on the ideXlab platform.
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mobile robot localization in a Structured Environment cluttered with obstacles
International Conference on Robotics and Automation, 1992Co-Authors: A A Holenstein, M A Muller, E BadreddinAbstract:The authors describe a method for mobile robot localization in an a priori known Structured Environment cluttered with unknown obstacles. The method is nearly independent of the number of obstacles encountered. An Environment model based on ultrasonic range readings was built and compared with the reference model using clustering techniques. The method is very robust and works well if only a few parts of the Environment are known. Results from an implementation on the mobile robot RAMSIS are presented. >
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ICRA - Mobile robot localization in a Structured Environment cluttered with obstacles
Proceedings 1992 IEEE International Conference on Robotics and Automation, 1Co-Authors: A A Holenstein, M A Muller, E BadreddinAbstract:The authors describe a method for mobile robot localization in an a priori known Structured Environment cluttered with unknown obstacles. The method is nearly independent of the number of obstacles encountered. An Environment model based on ultrasonic range readings was built and compared with the reference model using clustering techniques. The method is very robust and works well if only a few parts of the Environment are known. Results from an implementation on the mobile robot RAMSIS are presented. >
Marc Carreras - One of the best experts on this subject based on the ideXlab platform.
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Occupancy grid mapping in an underwater Structured Environment
IFAC Proceedings Volumes (IFAC-PapersOnline), 2009Co-Authors: E. Hernandez, Angelos Mallios, Pere Ridao, Marc CarrerasAbstract:This paper presents practical results about the occupancy grid mapping of an underwater man-made Environment using a sensor suite commonly available in nowadays Autonomous Underwater Vehicles (AUVs). The proposed algorithms are tested to be incorporated as part of the design of a new motion control system to integrate reactive obstacle avoidance with local path planning techniques to provide safe real-time guidance capabilities. The paper focus on the use of a sonar scan matching improved dead-reckoning navigation (Doppler Velocity Log (DVL) and Motion Reference Unit (MRU) based) together with an standard occupancy grid mapping algorithm. A conventional inverse sensor model for a sonar profiler is used and compared against a new inverse sensor model proposed to take advantage of the use of widely available imaging sonars. The system is validated experimentally on a dataset gathered with an AUV guided along a 600m path within a marina Environment. © 2009 IFAC.
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vision based localization of an underwater robot in a Structured Environment
International Conference on Robotics and Automation, 2003Co-Authors: Marc Carreras, Pere Ridao, Rafael Garcia, Tudor NicoseviciAbstract:This paper presents a vision-based localization approach for an underwater robot in a Structured Environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system.
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IbPRIA - High-Accuracy Localization of an Underwater Robot in a~Structured Environment Using Computer Vision
Pattern Recognition and Image Analysis, 2003Co-Authors: Marc Carreras, Pere Ridao, Joan Batlle, David RibasAbstract:This paper presents a vision-based localization approach for an underwater robot in a Structured Environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down-looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle. The paper details the codification used in the pattern and the localization algorithm, which is illustrated with some images. Finally, the paper shows results about the accuracy of the system.
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AUV Navigation in a Structured Environment Using Computer Vision
IFAC Proceedings Volumes, 2003Co-Authors: Marc Carreras, Pere Ridao, Joan Batlle, X. CufiAbstract:Abstract This paper presents a vision-based navigation approach for an underwater robot in a Structured Environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down-looking camera. Main features are, absolute and map-based navigation, landmark detection and tracking, and real-tirne computation (12.5 Hz). The proposed system proyides three-dirnensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity based low level controller. The paper details the navigation algorithm and shows some results.
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An EKF vision-based navigation of an UUV in a Structured Environment
IFAC Proceedings Volumes, 2003Co-Authors: David Ribas, Marc Carreras, Pere Ridao, X. CufiAbstract:Abstract This paper presents a vision-based navigation system for an underwater robot in a Structured Environment. The system is based in a coded pattern placed on the bottom of a water tank and an onboard down looking camera. The system provides three dimensional position and orientation of the vehicle. Accuracy of the drift-free estimate of the position is very high, with low noise effects. An extended Kalman filter based on the dynamic model of the robot is used to improve position and velocity estimation.
Shuguang Xiong - One of the best experts on this subject based on the ideXlab platform.
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efficient algorithms for sensor deployment and routing in sensor networks for network Structured Environment monitoring
International Conference on Computer Communications, 2012Co-Authors: Shuguang Xiong, Haiying Shen, Chen WangAbstract:When monitoring Environments with wireless sensor networks, optimal sensor deployment is a fundamental issue and an effective means to achieve desired performance. Selecting best sensor deployment has a dependence on the deployment Environments. Existing works address sensor deployment within three types of Environments including one dimensional line, 2-D field and 3-D space. However, in many applications the deployment Environments usually have network structures, which cannot be simply classified as the three types. The deployed locations and communications of sensor nodes are limited onto the network edges, which make the deployment problem distinct from that in other types of Environments. In this paper, we study sensor deployment in network-Structured Environments and aim to achieve k-coverage while minimizing the number of sensor nodes. Furthermore, we jointly consider the optimization of sink deployment and routing strategies with the goal to minimize the network communication cost of data collection. To the best of our knowledge, this paper is the first one to tackle sensor/sink deployment under the deployment constraints imposed by the network structure. The hardness of the problems is shown. Polynomial-time algorithms are proposed to determine optimal sensor/sink deployment and routing strategies in tree-topology network structure. Efficient approximation algorithms are proposed for the general graph network structure and their performances are analyzed. Theoretical results and extensive simulations show the efficiency of the proposed algorithms.
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INFOCOM - Efficient algorithms for sensor deployment and routing in sensor networks for network-Structured Environment monitoring
2012 Proceedings IEEE INFOCOM, 2012Co-Authors: Shuguang Xiong, Haiying Shen, Chen WangAbstract:When monitoring Environments with wireless sensor networks, optimal sensor deployment is a fundamental issue and an effective means to achieve desired performance. Selecting best sensor deployment has a dependence on the deployment Environments. Existing works address sensor deployment within three types of Environments including one dimensional line, 2-D field and 3-D space. However, in many applications the deployment Environments usually have network structures, which cannot be simply classified as the three types. The deployed locations and communications of sensor nodes are limited onto the network edges, which make the deployment problem distinct from that in other types of Environments. In this paper, we study sensor deployment in network-Structured Environments and aim to achieve k-coverage while minimizing the number of sensor nodes. Furthermore, we jointly consider the optimization of sink deployment and routing strategies with the goal to minimize the network communication cost of data collection. To the best of our knowledge, this paper is the first one to tackle sensor/sink deployment under the deployment constraints imposed by the network structure. The hardness of the problems is shown. Polynomial-time algorithms are proposed to determine optimal sensor/sink deployment and routing strategies in tree-topology network structure. Efficient approximation algorithms are proposed for the general graph network structure and their performances are analyzed. Theoretical results and extensive simulations show the efficiency of the proposed algorithms.
A Perez - One of the best experts on this subject based on the ideXlab platform.
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effects of dissipation on an adiabatic quantum search algorithm
New Journal of Physics, 2010Co-Authors: Ines De Vega, Mari Carmen Banuls, A PerezAbstract:According to recent studies (Amin et al 2008 Phys. Rev. Lett. 100 060503), the effect of a thermal bath may improve the performance of a quantum adiabatic search algorithm. In this paper, we compare the effects of such a thermal Environment on the algorithm performance with those of a Structured Environment similar to the one encountered in systems coupled to an electromagnetic field that exists within a photonic crystal. Whereas for all the parameter regimes explored here, the algorithm performance is worsened by contact with a thermal Environment, the picture appears to be different when one considers a Structured Environment. In this case we show that by tuning the Environment parameters to certain regimes, the algorithm performance can actually be improved with respect to the closed system case. Additionally, the relevance of considering the dissipation rates as complex quantities is discussed in both cases. More specifically, we find that the imaginary part of the rates cannot be neglected with the usual argument that it simply amounts to an energy shift and in fact influences crucially the system dynamics.
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effects of dissipation in an adiabatic quantum search algorithm
arXiv: Quantum Physics, 2010Co-Authors: Ines De Vega, Mari Carmen Banuls, A PerezAbstract:We consider the effect of two different Environments on the performance of the quantum adiabatic search algorithm, a thermal bath at finite temperature, and a Structured Environment similar to the one encountered in systems coupled to the electromagnetic field that exists within a photonic crystal. While for all the parameter regimes explored here, the algorithm performance is worsened by the contact with a thermal Environment, the picture appears to be different when considering a Structured Environment. In this case we show that, by tuning the Environment parameters to certain regimes, the algorithm performance can actually be improved with respect to the closed system case. Additionally, the relevance of considering the dissipation rates as complex quantities is discussed in both cases. More particularly, we find that the imaginary part of the rates can not be neglected with the usual argument that it simply amounts to an energy shift, and in fact influences crucially the system dynamics.
