Human-Assisted Virtual Environment Modeling for Robots

In order to avoid the complex calculation and poor robustness in automatic visual modeling process, a man-machine interaction based stereo vision system is developed for modeling an unknown environment. The operator's knowledge about a scene is used as a guidance for modeling 3D environment. The modeling technique has advantage in terms of reliability and robustness over other automatic modeling approaches. The data points needed for modeling an objects are obtained through the intersection of lines, or calculation from equations of curve, derived via fitting from human guided edge detection. The modeling accuracy is ensured by using image feature extraction. A multi-viewpoint modeling approach has been developed in order to deal with occlusion problems.Both accuracy and speed issues are addressed in this paper. The system implementation and some 3D measurements on real scene have been performed using cameras lenses of 16 mm and 8 mm with an accuracy 0.5 mm and 0.8 mm over the field of view, respectively. The virtual environment rendering based on the modeling data of real scenes with known model of mobile robot is given at the end of this paper.