We propose a support system of range data acquisition by a laser rangefinder for wide area outdoor modeling
in order to reduce un-observed portions of generated model. The system presents the operator a recommendation
degree map which illustrates recommendation position of acquisition of range data in the objective area.
The operator decides a next acquisition position in consideration of movement distance of sensor system and
recommendation degrees of the map. The recommendation degree is computed by measurement density as the
index. The recommendation degree at a position is given by the difference between measurement density acquired
by rangefinder and measurement density estimated by the system in reachable area of the laser beams.
The reachable area of the laser beams is estimated by using a 3D model generated from the acquired range data.
The system computes the measurement density by the reachable area of the laser beams. The recommendation
degrees in the objective area are computed by the model generated from range data whenever a range data is
acquired. Moreover, the system judges whether overlapping portions of the range data can be acquired for the
registration by ICP algorithm from a work area which the sensor system can enter.
This paper describes a 3D modeling method for wide area outdoor environments which is based on integrating omnidirectional range and color images. In the proposed method, outdoor scenes can be efficiently digitized by an omnidirectional laser rangefinder which can obtain a 3D shape with high-accuracy and an omnidirectional multi-camera system (OMS) which can capture a high-resolution color image.
Multiple range images are registered by minimizing the distances between corresponding points in the different range images. In order to register multiple range images stably, the points on the plane portions detected from the range data are used in registration process. The position and orientation acquired by the RTK-GPS and the gyroscope are used as initial value of simultaneous registration.
The 3D model which is obtained by registration of range data is mapped by the texture selected from omnidirectional images in consideration of the resolution of the texture and occlusions of the model. In experiments, we have carried out 3D modeling of our campus with the proposed method.