Proactive 3D Robotic Mapping using a RGB-D Sensor
Map building is a fundamental problem in autonomous robots. Using an inexpensive RGB-D camera, a 3D map can be built by solving the Simultaneous Localization and Mapping (SLAM) problem. However, the mapping will easily fail if there are not a sufficient number of features. In this project, a proactive 3D mapping framework is proposed using a mobile robot platform equipped with a RGB-D camera and a projector. Both the camera and the projector are mounted on pan-tilt units controlled by servo motors. With the motion of the camera pan-tilt unit and the movement of the robot, a binary hypothesis testing is modelled to evaluate the estimation accuracy of the camera pose. A pattern is generated by the projector to increase the number of features when the pose estimation has large errors based on the real-time evaluation. Two sets of experiments are conducted and the results show that the proposed approach improves the mapping performance in an indoor environment with sparse features.
The hardware setup of the proactive 3D robotic mapping system
A 3D map created by our robot
Another 3D map created by our robot
 J. Du, Y. OU and W. Sheng, Improving 3D Indoor Mapping with Motion Data, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO 2012).