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This paper proposes a 1-dimensional implementation of area-based stereo matching with minimal resource utilization. It achieves an acceptable disparity map without the use of expensive resources. The matching accuracy for the approach can in some extent even outperform that of its 2-dimensional counterpart. Additionally, as it excels in terms of frame rate and resource utilization, it is highly suitable for real-time stereo-vision systems.

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This paper proposes a stereo vision based localization and mapping strategy for vehicular navigation within industrial environments using natural landmarks. The work proposed is strictly related to factory automation, since focus is on industrial vehicle autonomous navigation for material handling, in order to increase the operating efficiency with reduced risk for accidents. The stereovision system, proposed as the main sensor, provides the necessary feedback to navigate and simultaneously calibrate the stereocamera parameters (like the camera separation, focal length, camera placement with respect to the robot, etc.). It uses the natural landmarks already present in the environment without additional infrastructures. Some simulation and experimental results are presented in order to explain the proposed method and current status.