The exploration and three dimension map building of mobile robot tasks in an unknown environment are normally do not have any future reference information. The mobile robot has to estimate positions and poses itself. Finding the distinguishable objects in environment are also required in order to create the pose reference points. Therefore, the selected sensors and register mapping algorithm are significant. The sensors which can provide both of depth and image data are still deficient. Recently, the Photonic Mixture Device camera (PMD) is a three dimension sensor which generates real-time high rate volume output of surrounding scenario as well as gray scale data. However, one PMD camera drawback is low resolution output. From this problem, the idea to fusion another high resolution CCD camera to PMD depth data is purposed. In this study hence presents the mobile robot exploration using integration of CCD and PMD camera in order to create the three dimension mapping. The Iterative Closest Point (ICP) algorithm is used for matching clouding points and minimizing the interval pose of the two scans. Eventually, the difference three dimension mapping output between fusion CCD camera and use only pure depth data are presented and evaluated.
