IEEE Transactions on Pattern Analysis and Machine Intelligence
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-dimensional signal and image processing
Two-dimensional signal and image processing
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Robot Motion Planning
Appearance-Based Obstacle Detection with Monocular Color Vision
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
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Vision navigation [1] has been a significant research area in recent year for robotic industrial. Various algorithms for obstacle detection and avoidance have been developed. Successfully testing of these algorithms require implementation in a realistic robot vehicle, which demands extra effort for researcher. The developed integrated autonomous guided vehicle [2] simulator and implementer (AGV-SI) emulates the realistic robot vehicle operating environment. Researchers can develop the algorithms based on the commonly used language - Matlab. Then simply input the algorithm and testing environment settings into the AGV-SI, an evaluation result is obtained. With the AGV-SI user can also choose to practically implement the algorithm by downloading the algorithm into a robot vehicle connected to the PC. With the support of the AGV-SI a novel algorithm was developed with the integration of adaptive median filter [3], inverse perspective map [4] and edge detection techniques. Both simulation and practical implementation validate the feasibility of the algorithm.