In view-based navigation, view sequences are constructed by considering only the appearance of images. This approach can work only in limited situation, because the structure of environment and camera poses with 3D camera motion is not considered. In this paper, we construct a multi sensor system using an omnidirectional camera, a motion sensor and laser range finders. Using this system, we propose a method of construction view sequence, that takes 3D camera poses into account.

In this paper, we present a system to automatically create a 3D map of city's buildings. The system consists of a laser range finder to measure distance between the sensor set and the building; and also a fish-eye-lens camera to measure the height of the buildings while capturing the texture of the model. Our system allows not only capturing the geometry of the buildings, but also how the buildings would look like on a street-level view. This allows for the creation of a 3D model that is suitable for navigation purposes.

This paper describes 3D environment modeling and camera pose estimation system by using a single camera. Because a wide angle camera provides a wide field of view at once, it enables the system to acquire reconstruction results stably. Moreover, a camera which has advantages of small size and light weight, is easily considered to apply the system to a portable sensor. We constructed environment modeling and camera pose estimation system by means of SFM approach (8 point algorithm, bundle adjustment and motion stereo). Graph slam is also adapted to smooth the reconstruction results. Experiments were performed in indoor environment, we comfirmed the capability of the reconstruction ability of a wide angle camera.

In this paper, we present a method to obtain the depth of the building using a satellite image of Google Earth and GPS receiver. Maps with 3D information are useful for robot navigation. This method is based on "3D Street View", which is a 3D model of the building automatically created with laser range finder and fish eye lens camera.

In View-based Navigation, view sequence are constructed considering with only appearance of images. This aproach can work only in limited situation because there are no consideration about structure of environment and camera poses with 3D camera motion. In this paper, We construct multi sensor system using omnidirectional camera, motion sensor and laser range finder, and propose a method of construction view sequence considering about 3D environment and camera poses.