To realize the obstacle avoidance and automatic navigation of a robot in a low texture environment, an active stereo visual system consisting a binocular camera and a compact laser projector was established. The dense stereo matching algorithm was investigated. Firstly, the compact laser projector generated the spot patterns with excellent uniqueness and anti-noise performance for increasing the texture information. Then, an adaptive-window matching algorithm was proposed based on Integral Grayscale Variance(IGSV)and Integral Gradient Variance(IGV). The algorithm was used calculate the integral variance in a matching window using the integral image obtained by the left image. If it was greater than the variance threshold, the correlation between the left and right image pixels was calculated to get the dense disparity maps. Experimental results show that the vision system accurately gets the 3D dense scene around the robot and the 3D reconstruction accuracy is 0.16 mm, which is suitable for the obstacle avoidance and automatic navigation. As compared with the traditional methods, the computation cost of dense matching has at least decreased by 93% since the computation used for image variance could not increase with the size of the matching window.