24 November 2014 Fast obstacle detection based on multi-sensor information fusion
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Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 93011K (2014) https://doi.org/10.1117/12.2072152
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China
Abstract
Obstacle detection is one of the key problems in areas such as driving assistance and mobile robot navigation, which cannot meet the actual demand by using a single sensor. A method is proposed to realize the real-time access to the information of the obstacle in front of the robot and calculating the real size of the obstacle area according to the mechanism of the triangle similarity in process of imaging by fusing datum from a camera and an ultrasonic sensor, which supports the local path planning decision. In the part of image analyzing, the obstacle detection region is limited according to complementary principle. We chose ultrasonic detection range as the region for obstacle detection when the obstacle is relatively near the robot, and the travelling road area in front of the robot is the region for a relatively-long-distance detection. The obstacle detection algorithm is adapted from a powerful background subtraction algorithm ViBe: Visual Background Extractor. We extracted an obstacle free region in front of the robot in the initial frame, this region provided a reference sample set of gray scale value for obstacle detection. Experiments of detecting different obstacles at different distances respectively, give the accuracy of the obstacle detection and the error percentage between the calculated size and the actual size of the detected obstacle. Experimental results show that the detection scheme can effectively detect obstacles in front of the robot and provide size of the obstacle with relatively high dimensional accuracy.
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Linli Lu, Linli Lu, Jie Ying, Jie Ying, } "Fast obstacle detection based on multi-sensor information fusion", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93011K (24 November 2014); doi: 10.1117/12.2072152; https://doi.org/10.1117/12.2072152
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