Suchergebnisse

In this paper we address the issue of autonomous navigation, that is, the ability for a navigation system to provide information about the states of a vehicle without the need for a priori infrastructures such as GPS, beacons, or preloaded maps of the area of interest. The algorithm applied is known as Simultaneous Localisation and Mapping (SLAM). It is a terrain aided navigation system which has the capability for online map building, while simultaneously utilising the generated map to bound the errors in the navigation solution. As no a priori terrain information nor initial knowledge of the vehicle location is required, this algorithm presents a powerful navigation augmentation system. More importantly, it can be implemented as an independent navigation system. This paper also describes a decentralised SLAM algorithm which allows multiple vehicles to acquire a joint 3D map via a decentralised information fusion network. The key idea behind this decentralised SLAM is to represent the map in information form (negative log-likelihood) for communication. Experimental results are provided using computer simulation to demonstrate the single-vehicle and multi-vehicles SLAM without the use of GPS and preloaded maps. ; This work is supported in part by the ARC Centre of Excellence programme, funded by the Australian Research Council (ARC) and the New South Wales State Government. The Autonomous Navigation and Sensing Experimental Research (ANSER) Project is funded by BAE SYSTEMS UK and BAE SYSTEMS Australia.

In this paper we address the issue of autonomous navigation, that is, the ability for a navigation system to provide information about the states of a vehicle without the need for a priori infrastructures such as GPS, beacons, or preloaded maps of the area of interest. The algorithm applied is known as Simultaneous Localisation and Mapping (SLAM). It is a terrain aided navigation system which has the capability for online map building, while simultaneously utilising the generated map to bound the errors in the navigation solution. As no a priori terrain information nor initial knowledge of the vehicle location is required, this algorithm presents a powerful navigation augmentation system. More importantly, it can be implemented as an independent navigation system. This paper also describes a decentralised SLAM algorithm which allows multiple vehicles to acquire a joint 3D map via a decentralised information fusion network. The key idea behind this decentralised SLAM is to represent the map in information form (negative log-likelihood) for communication. Experimental results are provided using computer simulation to demonstrate the single-vehicle and multi-vehicles SLAM without the use of GPS and preloaded maps. ; This work is supported in part by the ARC Centre of Excellence programme, funded by the Australian Research Council (ARC) and the New South Wales State Government. The Autonomous Navigation and Sensing Experimental Research (ANSER) Project is funded by BAE SYSTEMS UK and BAE SYSTEMS Australia.