3D feature extraction by integrating Laser Scanner and CCD Sensor with IMU for an unmanned Helicopter Platform
Masahiko Nagai, Ryosuke Shibasaki, Dinesh Manandhar, Huijing Zhao
Center for Spatial Information Science, The University of Tokyo
Cw-503, IIS, 4-6-1, Komaba, Meguro-ku, Tokyo 153-8505, Japan
Tel: +81-3-5452-6417 Fax: +81-3-5452-6414
Email: nagaim@iis.u-tokyo.ac.jp
Hideo Kumagai, Shintaro Mizukami
Tamagawa Seiki Co., Ltd. 1879 Ohyasumi, Iida-City, Nagano 395-8515, Japan
Abstract
Three dimension data are in great demand for the various applications such as 3D GIS,
navigation, digital archive, simulation, computer games and so on. In order to represent 3D
space and moving objects in details, it is indispensable to acquire 3D shape and texture together
efficiently. However, there still lack a reliable, quick and cheap method for acquiring three
dimension data of objects with higher resolution and accuracy in outdoor environment. In this
research, we propose a combination of a digital camera and a laser scanner with low-cost IMU
(Inertial Measurement Unit) for unmanned helicopters.
3D shape is acquired by a laser scanner as point cloud data, and images are acquired by CCD
sensor from the same platform simultaneously. Positioning data is acquired by GPS and IMU.
All the sensors are synchronized with movement or attitude of the platform. Calibration of laser
scanner and CCD camera is conducted to know the relative position and attitude of each sensor
against GPS and IMU. Through Kalman filter, an optimal estimate of the sensor position and
attitude are estimated from GPS and IMU. Using the CCD images, bundle block adjustment
conducted to aid Kalman filter by initialization of position and attitude. The combination of
bundle block adjustment and Kalman filter for precise positioning is proposed in this research.
Using this measurement system, sensor position and attitude for mapping are basically acquired
by GPS/IMU and their errors are complemented by CCD images using tie points. Colors are
assigned to laser points based on the CCD image color.
Points cloud model is produced for rendering objects with rich shape and detailed texture for
feature extraction. Geometric shape, which is acquired by leaser scanner, represents features.
Color information, which is acquired by CCD sensor, details those features. That is, more detail
extraction is possible using both 3D shapes and colors.
1. Introduction
The mobile mapping has been developed since late 1980's. The development of the mobile
mapping system becomes possible due to the availability of GPS and IMU (Kumagai, H., Kubo,
Y., 2002). In this research, the combination of a CCD sensor and a small (cheap) laser scanner
with an inexpensive IMU and GPS for mobile platform are proposed. Utilization of mobile
platform is very important for acquiring data effectively (Zhao, H., Shibasaki, R., 2001). That is,
it is necessary to consider the method to get to develop the high precision positioning system in
moving environment. In this research, direct geo-referencing is achieved automatically from
mobile platform without any ground control points. Here, a "direct" geo-referencing mean
geo-referencing that does not require ground control points. The methods of data acquisition and
digital surface modelling are developed with the method of direct geo-referencing. This leads to
rendering objects with rich shape and detailed texture automatically. Using these data, feature
extraction is conducted. More detailed extraction is possible using both laser range data and
CCD image.
