Add to ORKGIn this work, a real-time localization problem is formulated by incorporating exteroceptive sensors as sources of both relative state measurement and delayed information within a direct Kalman filtering approach. The problem of delayed incorporation of relative state measurements is addressed by extending the stochastic cloning framework, whereby an augmented state vector is defined by copies of the current and delayed states
State estimation in dynamical telepresence systemsis very important in real-world applications as th...
In this article, a multisensor joint localization system is proposed based on modified cubature Kalm...
A basic requirement for an autonomous mobile robot is to localize itself with repect to a given coor...
In this work, a real-time localization problem is formulated by incorporating exteroceptive sensors ...
Introduces a generalized framework, termed "stochastic cloning," for processing relative state measu...
This paper presents a new method to optimally combine motion measurements provided by proprioceptive...
When combining data from various sensors it is vital to acknowledge possible measurement delays. Fur...
One of the most important tasks for visual inertial odometry systems is pose estimation. By integrat...
Many systems include sensors with large measurement delays that must be fused in a Kalman filter in ...
This paper proposes an efficient real-time optimal estimation scheme that uses accurate but delayed ...
Originally, the Accumulated State Density (ASD) has been proposed to provide an exact solution to th...
In this paper we present a pedestrian navigation algorithm based on a Kalman filter that exploits re...
A fusion hierarchical state filtration with k−step delay sharing pattern for a multisensor system is...
Distributed state estimation under uncertain process and measurement noise covariances is considered...
Abstract-In target tracking, standard sensors as radar and vision observe the target with a negligib...
State estimation in dynamical telepresence systemsis very important in real-world applications as th...
In this article, a multisensor joint localization system is proposed based on modified cubature Kalm...
A basic requirement for an autonomous mobile robot is to localize itself with repect to a given coor...
In this work, a real-time localization problem is formulated by incorporating exteroceptive sensors ...
Introduces a generalized framework, termed "stochastic cloning," for processing relative state measu...
This paper presents a new method to optimally combine motion measurements provided by proprioceptive...
When combining data from various sensors it is vital to acknowledge possible measurement delays. Fur...
One of the most important tasks for visual inertial odometry systems is pose estimation. By integrat...
Many systems include sensors with large measurement delays that must be fused in a Kalman filter in ...
This paper proposes an efficient real-time optimal estimation scheme that uses accurate but delayed ...
Originally, the Accumulated State Density (ASD) has been proposed to provide an exact solution to th...
In this paper we present a pedestrian navigation algorithm based on a Kalman filter that exploits re...
A fusion hierarchical state filtration with k−step delay sharing pattern for a multisensor system is...
Distributed state estimation under uncertain process and measurement noise covariances is considered...
Abstract-In target tracking, standard sensors as radar and vision observe the target with a negligib...
State estimation in dynamical telepresence systemsis very important in real-world applications as th...
In this article, a multisensor joint localization system is proposed based on modified cubature Kalm...
A basic requirement for an autonomous mobile robot is to localize itself with repect to a given coor...