Add to ORKGSummary. Decentralised estimation of heterogeneous sensors is performed on an outdoor network. Attributes such as position, appearance, and identity represented by non-Gaussian distributions are used in in the fusion process. It is shown here that real-time decentralised data fusion of non-Gaussian estimates can be used to build rich environmental maps. Human operators are also used as additional sensors in the network to complement robotic information.
Network architectures Distributed estimation An introduction to Sensor Networks In recent years, gre...
In this paper, we focus on large-scale environment monitoring by utilizing a fully decentralized tea...
Multi-Agent Systems (MAS) can be used in the exploration and mapping of unknown environments. To coo...
This paper presents the development and demonstration of non-Gaussian, decentralised state estimatio...
Abstract-Networks of environmental sensors are playing an increasingly important role in scientific ...
The appeal of distributed sensing and computation is matched by the formidable challenges it present...
This paper presents a scalable Bayesian technique for decentralized state estimation from multiple...
This thesis explores data fusion and distributed robotic perception through a series of theoretical ...
Centralized state-estimation algorithms, such as the original Kalman filter, are no longer feasible ...
Centralized state-estimation algorithms, such as the original Kalman filter, are no longer feasible ...
This paper presents the design of a probabilistic model of human perception as an integral part of a...
Many physical, geological and environmental phenomena are spread over large spatio-temporal scales a...
An important research area in sensor networks is the design and analysis of distributed estimation a...
An important research area in sensor networks is the design and analysis of distributed estimation a...
An important research area in sensor networks is the design and analysis of distributed estimation a...
Network architectures Distributed estimation An introduction to Sensor Networks In recent years, gre...
In this paper, we focus on large-scale environment monitoring by utilizing a fully decentralized tea...
Multi-Agent Systems (MAS) can be used in the exploration and mapping of unknown environments. To coo...
This paper presents the development and demonstration of non-Gaussian, decentralised state estimatio...
Abstract-Networks of environmental sensors are playing an increasingly important role in scientific ...
The appeal of distributed sensing and computation is matched by the formidable challenges it present...
This paper presents a scalable Bayesian technique for decentralized state estimation from multiple...
This thesis explores data fusion and distributed robotic perception through a series of theoretical ...
Centralized state-estimation algorithms, such as the original Kalman filter, are no longer feasible ...
Centralized state-estimation algorithms, such as the original Kalman filter, are no longer feasible ...
This paper presents the design of a probabilistic model of human perception as an integral part of a...
Many physical, geological and environmental phenomena are spread over large spatio-temporal scales a...
An important research area in sensor networks is the design and analysis of distributed estimation a...
An important research area in sensor networks is the design and analysis of distributed estimation a...
An important research area in sensor networks is the design and analysis of distributed estimation a...
Network architectures Distributed estimation An introduction to Sensor Networks In recent years, gre...
In this paper, we focus on large-scale environment monitoring by utilizing a fully decentralized tea...
Multi-Agent Systems (MAS) can be used in the exploration and mapping of unknown environments. To coo...