The Experts below are selected from a list of 8514 Experts worldwide ranked by ideXlab platform
Mehrzad Namvar - One of the best experts on this subject based on the ideXlab platform.
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global attitude Position estimation using Landmark and biased velocity measurements
IEEE Transactions on Aerospace and Electronic Systems, 2016Co-Authors: Amir Moeini, Mehrzad NamvarAbstract:We propose an observer for attitude and Position estimation of a rigid body using translational and angular velocity measurements together with a single Landmark. Under an observability condition depending on Landmark Position, global and asymptotic convergence of attitude and Position estimation errors to zero is achieved. We extend the observer for the case of nonideal velocity measurements. Simulation examples demonstrate convergence properties of the observer in the face of noise and bias in velocity measurements.
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Global attitude/Position estimation using Landmark and biased velocity measurements
IEEE Transactions on Aerospace and Electronic Systems, 2016Co-Authors: Amir Moeini, Mehrzad NamvarAbstract:We propose an observer for attitude and Position estimation of a rigid body using translational and angular velocity measurements together with a single Landmark. Under an observability condition depending on Landmark Position, global and asymptotic convergence of attitude and Position estimation errors to zero is achieved. We extend the observer for the case of nonideal velocity measurements. Simulation examples demonstrate convergence properties of the observer in the face of noise and bias in velocity measurements.
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global estimation of rigid body attitude Position using a single Landmark and biased velocity measurements
Conference on Decision and Control, 2014Co-Authors: Amir Moeini, Mehrzad NamvarAbstract:In this paper we propose an observer for attitude and Position estimation of a rigid body using data provided by rate gyros, Doppler sensors and a single Landmark measurement. Under an observability condition which depends on Landmark Position, asymptotic convergence of the observer is proved. The initial attitude and Position estimates can assume any values and hence the convergence is in global sense. We extend the observer for the case of non-ideal translational and angular velocity measurements. Simulation examples demonstrate Position and attitude estimation in two cases: a single moving Landmark, and three fixed Landmarks.
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CDC - Global estimation of rigid-body attitude/Position using a single Landmark and biased velocity measurements
53rd IEEE Conference on Decision and Control, 2014Co-Authors: Amir Moeini, Mehrzad NamvarAbstract:In this paper we propose an observer for attitude and Position estimation of a rigid body using data provided by rate gyros, Doppler sensors and a single Landmark measurement. Under an observability condition which depends on Landmark Position, asymptotic convergence of the observer is proved. The initial attitude and Position estimates can assume any values and hence the convergence is in global sense. We extend the observer for the case of non-ideal translational and angular velocity measurements. Simulation examples demonstrate Position and attitude estimation in two cases: a single moving Landmark, and three fixed Landmarks.
Amir Moeini - One of the best experts on this subject based on the ideXlab platform.
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global attitude Position estimation using Landmark and biased velocity measurements
IEEE Transactions on Aerospace and Electronic Systems, 2016Co-Authors: Amir Moeini, Mehrzad NamvarAbstract:We propose an observer for attitude and Position estimation of a rigid body using translational and angular velocity measurements together with a single Landmark. Under an observability condition depending on Landmark Position, global and asymptotic convergence of attitude and Position estimation errors to zero is achieved. We extend the observer for the case of nonideal velocity measurements. Simulation examples demonstrate convergence properties of the observer in the face of noise and bias in velocity measurements.
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Global attitude/Position estimation using Landmark and biased velocity measurements
IEEE Transactions on Aerospace and Electronic Systems, 2016Co-Authors: Amir Moeini, Mehrzad NamvarAbstract:We propose an observer for attitude and Position estimation of a rigid body using translational and angular velocity measurements together with a single Landmark. Under an observability condition depending on Landmark Position, global and asymptotic convergence of attitude and Position estimation errors to zero is achieved. We extend the observer for the case of nonideal velocity measurements. Simulation examples demonstrate convergence properties of the observer in the face of noise and bias in velocity measurements.
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global estimation of rigid body attitude Position using a single Landmark and biased velocity measurements
Conference on Decision and Control, 2014Co-Authors: Amir Moeini, Mehrzad NamvarAbstract:In this paper we propose an observer for attitude and Position estimation of a rigid body using data provided by rate gyros, Doppler sensors and a single Landmark measurement. Under an observability condition which depends on Landmark Position, asymptotic convergence of the observer is proved. The initial attitude and Position estimates can assume any values and hence the convergence is in global sense. We extend the observer for the case of non-ideal translational and angular velocity measurements. Simulation examples demonstrate Position and attitude estimation in two cases: a single moving Landmark, and three fixed Landmarks.
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CDC - Global estimation of rigid-body attitude/Position using a single Landmark and biased velocity measurements
53rd IEEE Conference on Decision and Control, 2014Co-Authors: Amir Moeini, Mehrzad NamvarAbstract:In this paper we propose an observer for attitude and Position estimation of a rigid body using data provided by rate gyros, Doppler sensors and a single Landmark measurement. Under an observability condition which depends on Landmark Position, asymptotic convergence of the observer is proved. The initial attitude and Position estimates can assume any values and hence the convergence is in global sense. We extend the observer for the case of non-ideal translational and angular velocity measurements. Simulation examples demonstrate Position and attitude estimation in two cases: a single moving Landmark, and three fixed Landmarks.
Marleen De Bruijne - One of the best experts on this subject based on the ideXlab platform.
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comparison of shape regression methods under Landmark Position uncertainty
Medical Image Computing and Computer-Assisted Intervention, 2011Co-Authors: Nora Baka, Coert Metz, Michiel Schaap, Boudewijn P F Lelieveldt, Wiro J Niessen, Marleen De BruijneAbstract:Despite the growing interest in regression based shape estimation, no study has yet systematically compared different regression methods for shape estimation. We aimed to fill this gap by comparing linear regression methods with a special focus on shapes with Landmark Position uncertainties. We investigate two scenarios: In the first, the uncertainty of the Landmark Positions was similar in the training and test dataset, whereas in the second the uncertainty of the training and test data were different. Both scenarios were tested on simulated data and on statistical models of the left ventricle estimating the end-systolic shape from end-diastole with Landmark uncertainties derived from the segmentation process, and of the femur estimating the 3D shape from one projection with Landmark uncertainties derived from the imaging setup. Results show that in the first scenario linear regression methods tend to perform similar. In the second scenario including estimates of the test shape Landmark uncertainty in the regression improved results.
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MICCAI (2) - Comparison of shape regression methods under Landmark Position uncertainty
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Inte, 2011Co-Authors: Nora Baka, Coert Metz, Michiel Schaap, Boudewijn P F Lelieveldt, Wiro J Niessen, Marleen De BruijneAbstract:Despite the growing interest in regression based shape estimation, no study has yet systematically compared different regression methods for shape estimation. We aimed to fill this gap by comparing linear regression methods with a special focus on shapes with Landmark Position uncertainties. We investigate two scenarios: In the first, the uncertainty of the Landmark Positions was similar in the training and test dataset, whereas in the second the uncertainty of the training and test data were different. Both scenarios were tested on simulated data and on statistical models of the left ventricle estimating the end-systolic shape from end-diastole with Landmark uncertainties derived from the segmentation process, and of the femur estimating the 3D shape from one projection with Landmark uncertainties derived from the imaging setup. Results show that in the first scenario linear regression methods tend to perform similar. In the second scenario including estimates of the test shape Landmark uncertainty in the regression improved results.
Benjamin L De Bivort - One of the best experts on this subject based on the ideXlab platform.
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ring attractor dynamics emerge from a spiking model of the entire protocerebral bridge
Frontiers in Behavioral Neuroscience, 2017Co-Authors: Kyobi S Kakaria, Benjamin L De BivortAbstract:Animal navigation is accomplished by a combination of Landmark-following and dead reckoning based on estimates of self motion. Both of these approaches require the encoding of heading information, which can be represented as an allocentric or egocentric azimuthal angle. Recently, Ca2+ correlates of Landmark Position and heading direction, in egocentric coordinates, were observed in the ellipsoid body (EB), a ring-shaped processing unit in the fly central complex (Seelig and Jayaraman, 2015). These correlates displayed key dynamics of so-called ring attractors, namely: 1) responsiveness to the Position of external stimuli, 2) persistence in the absence of external stimuli, 3) locking onto a single external stimulus when presented with two competitors, 4) stochastically switching between competitors with low probability, and 5) sliding or jumping between Positions when an external stimulus moves. We hypothesized that ring attractor-like activity in the EB arises from reciprocal neuronal connections to a related structure, the protocerebral bridge (PB). Using recent light-microscopy resolution catalogues of neuronal cell types in the PB (Wolff et al., 2015; Lin et al., 2013), we determined a connectivity matrix for the PB-EB circuit. When activity in this network was simulated using a leaky-integrate-and-fire model, we observed patterns of activity that closely resemble the reported Ca2+ phenomena. All qualitative ring attractor behaviors were recapitulated in our model, allowing us to predict failure modes of the putative PB-EB ring attractor and the circuit dynamics phenotypes of thermogenetic or optogenetic manipulations. Ring attractor dynamics emerged under a wide variety of parameter configurations, even including non-spiking leaky-integrator implementations. This suggests that the ring-attractor computation is a robust output of this circuit, apparently arising from its high-level network properties (topological configuration, local excitation and long-range inhibition) rather than fine-scale biological detail.
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ring attractor dynamics emerge from a spiking model of the entire protocerebral bridge
bioRxiv, 2016Co-Authors: Kyobi S Kakaria, Benjamin L De BivortAbstract:Animal navigation is accomplished by a combination of Landmark-following and dead reckoning based on estimates of self motion. Both of these approaches require the encoding of heading information, which can be represented as an allocentric or egocentric azimuthal angle. Recently, Ca2+ correlates of Landmark Position and heading direction, in egocentric coordinates, were observed in the ellipsoid body (EB), a ring-shaped processing unit in the fly central complex (Seelig and Jayaraman, 2015). These correlates displayed key dynamics of so-called ring attractors, namely: 1) responsiveness to the Position of external stimuli, 2) persistence in the absence of external stimuli, 3) locking onto a single external stimulus when presented with two competitors, 4) stochastically switching between competitors with low probability, and 5) sliding or jumping between Positions when an external stimulus moves. We hypothesized that ring attractor-like activity in the EB arises from reciprocal neuronal connections to a related structure, the protocerebral bridge (PB). Using recent light-microscopy resolution catalogues of neuronal cell types in the PB (Wolff et al., 2015; Lin et al., 2013), we determined a connectivity matrix for the PB-EB circuit. When activity in this network was simulated using a leaky-integrate-and-fire model, we observed patterns of activity that closely resemble the reported Ca2+ phenomena. All qualitative ring attractor behaviors were recapitulated in our model, allowing us to predict failure modes of the PB ring attractor and the circuit dynamic phenotypes of thermogenetic or optogenetic manipulations. Ring attractor dynamics emerged under a wide variety of parameter configurations, even including non-spiking leaky-integrator implementations. This suggests that the ring-attractor computation is a robust output of this circuit, apparently arising from its high-level network properties (topological configuration, local excitation and long-range inhibition) rather than biological nitty gritty.
Thomas Lemaire - One of the best experts on this subject based on the ideXlab platform.
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SLAM with panoramic vision
Journal of Field Robotics, 2007Co-Authors: Thomas Lemaire, Simon LacroixAbstract:This article presents an approach to SLAM that takes advantage of panoramic images. Landmarks are interest points detected and matched in the images and mapped according to a bearings-only SLAM approach. As they are acquired and processed, the panoramic images are also indexed and stored into a database. A database query procedure, independent of the robot and Landmark Position estimates, is able to detect loop closures by retrieving memorized images that are close to the current robot Position. The bearings-only estimation process is described, and results over a trajectory of a few hundreds of meters are presented and discussed.
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Undelayed Initialization in Bearing Only SLAM
2005Co-Authors: Joan Solà, André Monin, Michel Devy, Thomas LemaireAbstract:Most solutions to the SLAM problem in robotics have utilized Range and Bearing sensors as the provided perception data is easy to incorporate, allowing immediate Landmark initialization. This is not the case when using Bearing-Only information because the distance to the perceived Landmarks is not directly provided. A whole estimate of a Landmark Position will only be possible via a set of measurements taken from different points of view. The vast majority of contributions to this problem utilize a parallel task to get this estimate, and hence the Landmark initialization is delayed. We give a new insight to the problem and present a method to avoid this delay by initializing the whole ray that defines the direction of the Landmark. We utilize a minimal and computationally efficient form to represent this ray and a new strategy for the subsequent updates. Simulations have been carried out to validate the proposed algorithms.
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Undelayed initialization in bearing only SLAM
2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, 2005Co-Authors: Jordi Solà, Michel Devy, André Monin, Thomas LemaireAbstract:Most solutions to the SLAM problem in robotics have utilised range and beating sensors as the provided perception data is easy to incorporate, allowing immediate Landmark initialization. This is not the case when using bearing-only information because the distance to the perceived Landmarks is not directly provided. A whole estimate of a Landmark Position is only possible via a set of measurements taken from different points of view. The vast majority of contributions to this problem perform a parallel task to get this estimate, and hence the Landmark initialization is delayed. We give a new insight to the problem and present a method to avoid this delay by initializing the whole ray that defines the direction of the Landmark. We utilize a minimal and computationally efficient form to represent this ray and a new strategy for the subsequent updates. Simulations have been carried out to validate the proposed algorithms.
