Mobile robot 3D map building based on RTM

Under the structure of robot technology middleware(RTM), this paper presents a distributed method for mobile robot simultaneous localization and mapping(SLAM) to address the problem of 3D modeling in complex indoor environment.We integrate the image feature and depth information to establish the correspondence-based iterative closest point (ICP) algorithm for localizing the robot precisely. With the introduction of keyframe selection mechanism, a vision-based loop closure detect algorithm and tree-based network optimizer(TORO) are used to efficiently achieve globally consistent and accuracy maps during the map building. Experimental results verify the feasibility and effectiveness of the proposed algorithm in the indoor environment.