Towards Outdoor Localization Using GIS, Vision System andStochastic Error Propagation

Abstract : The paper presents a method for robot localization (the position and attitude of the robot with respect to a model) when a robot is on the move and does not necessarily have good gps coverage. The robot discussed in the paper is a remote controlled vehicle with a GIS database and an onboard camera. The method developed starts with an initial vehicle configuration (steering wheel angle, speed) and an initial point in the GIS mapped to an initial point in the camera's image. Then, for each small displacement of the vehicle, the linear and angular velocities are calculated and a formula developed in the paper for error adjustment is applied if there is a good gps reading. The result of the calculation is used to determine the uncertainty of the location and can be used along with the 3D GIS data to project areas of uncertainty for features of interest onto the camera image. For example, say the GIS data contains fire hydrants and the calculations show that there is a high degree of location uncertainty then the camera image will have an overlay of large ellipses around the fire hydrants whereas a small degree of uncertainty would have smaller ellipses around the fire hydrants. An experiment testing the method is discussed in the paper and there is also a good review of prior work on localization techniques.
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Mikael Kais, Stéphane Dauvillier, Arnaud de la Fortelle, Ichiro Masaki, Christian Laugier. Towards Outdoor Localization Using GIS, Vision System andStochastic Error Propagation. ICARA 2004 - 2nd International Conference on Autonomous Robots and Agents., Dec 2004, Palmerston North, New Zealand. pp.198-205. ⟨inria-00182121⟩

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