A sensor fusion scheme for mobile robot environment recognition that incorporates range data and contour data is proposed. Ultrasonic sensor provides coarse spatial description but guarantees open space (with no obstacle) within sonic cone with relatively high belief. Laser structured light system provides detailed contour description of environment but prone to light noise and is easily affected by surface reflectivity. We present a sensor fusion scheme that can compensate the disadvantages of both sensors. Line models from laser structured light system play a key role in environment description. Overall fusion process is composed of two stages: Noise elimination and belief updates. Dempster-Shafer's evidential reasoning is applied at each stage. Open space estimation from sonar range measurements brings elimination of noisy lines from laser sensor. Comparing actual sonar data to the simulated sonar data enables data of two disparate sensors be fused at the unified feature space. Experiments have been conducted to recognize a naturally cluttered indoor environment partially surrounded by window glasses. Experimental results demonstrate the effectiveness of the proposed method.