Publications related to Perception-aware Receding Horizon Navigation for MAVs

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This paper presents a novel distributed estimation algorithm based on the concept of moving horizon estimation. Under weak observability conditions we prove convergence of the state estimates computed by any sensors to the correct state even when constrain ...

2010

Moving horizon partition-based state estimation of large-scale systems

Giancarlo Ferrari Trecate, Marcello Farina

This paper presents three novel Moving Horizon Estimation (MHE) methods for discrete-time partitioned linear systems, i.e. systems decomposed into coupled subsystems with non-overlapping states. The MHE approach is used due to its capability of exploiting ...

2010

Learning in Gaussian Markov random fields

Thomas Riedl

This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown parameter. Thus in order to support the state estimator with prior information o ...

2010

Moving horizon state estimation of large-scale constrained partitioned systems

Giancarlo Ferrari Trecate, Marcello Farina

This paper presents three novel Moving Horizon Estimation (MHE) methods for discrete-time partitioned linear systems, i.e. systems decomposed into coupled subsystems with non-overlapping states. The MHE approach is used due to its capability of exploiting ...

2009

A moving horizon scheme for distributed state estimation

Giancarlo Ferrari Trecate, Marcello Farina

This paper presents a novel distributed estimation algorithm based on the concept of moving horizon estimation. Under weak observability conditions we prove convergence of the state estimates computed by any sensor to the correct state even when constraint ...

2009

A moving horizon scheme for distributed state estimation

Giancarlo Ferrari Trecate, Marcello Farina

This paper presents a novel distributed estimation algorithm based on the concept of moving horizon estimation. Under weak observability conditions we prove convergence of the state estimates computed by any sensor to the correct state even when constraint ...

2009

The IceCube data acquisition system: Signal capture, digitization, and timestamping

Xiaoxia Bai

IceCube is a km-scale neutrino observatory under construction at the South Pole with sensors both in the deep ice (InIce) and on the surface (IceTop). The sensors, called Digital Optical Modules (DOMs). detect, digitize and timestamp the signals from optic ...

2009

Modelling human perception of static facial expressions

Michel Bierlaire, Jean-Philippe Thiran, Matteo Sorci, Gianluca Antonini, Javier Cruz Mota, Barbara Cerretani

Data collected through a recent web-based survey show that the perception (i.e. labeling) of a human facial expression by a human observer is a subjective process, which results in a lack of a unique ground-truth, as intended in the standard classification ...

2008

Modelling human perception of static facial expressions

Michel Bierlaire, Jean-Philippe Thiran, Matteo Sorci, Gianluca Antonini, Javier Cruz Mota, Thomas Robin, Barbara Cerretani

Data collected through a recent web-based survey show that the perception (i.e. labeling) of a human facial expression by a human observer is a subjective process, which results in a lack of a unique ground-truth, as intended in the standard classificatio ...

2008

Vision-based inertial-aided navigation is gaining ground due to its many potential applications. In previous decades, the integration of vision and inertial sensors was monopolised by the defence industry due to its complexity and unrealistic economic burd ...

EPFL2006

Perception-aware Receding Horizon Navigation for MAVs

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Moving horizon partition-based state estimation of large-scale systems

Learning in Gaussian Markov random fields

Moving horizon state estimation of large-scale constrained partitioned systems

A moving horizon scheme for distributed state estimation

A moving horizon scheme for distributed state estimation

The IceCube data acquisition system: Signal capture, digitization, and timestamping

Modelling human perception of static facial expressions

Modelling human perception of static facial expressions

A moving horizon scheme for distributed state estimation

Moving horizon partition-based state estimation of large-scale systems

Moving horizon state estimation of large-scale constrained partitioned systems

A moving horizon scheme for distributed state estimation

The IceCube data acquisition system: Signal capture, digitization, and timestamping

Modelling human perception of static facial expressions

Modelling human perception of static facial expressions

Learning in Gaussian Markov random fields