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A novel improved probability-guided ransac algorithm for robot 3d map building
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نویسنده
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jia s. ,wang k. ,li x. ,xu t.
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منبع
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journal of sensors - 2016 - دوره : 2016 - شماره : 0
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چکیده
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This paper presents a novel improved ransac algorithm based on probability and ds evidence theory to deal with the robust pose estimation in robot 3d map building. in this proposed ransac algorithm,a parameter model is estimated by using a random sampling test set. based on this estimated model,all points are tested to evaluate the fitness of current parameter model and their probabilities are updated by using a total probability formula during the iterations. the maximum size of inlier set containing the test point is taken into account to get a more reliable evaluation for test points by using ds evidence theory. furthermore,the theories of forgetting are utilized to filter out the unstable inliers and improve the stability of the proposed algorithm. in order to boost a high performance,an inverse mapping sampling strategy is adopted based on the updated probabilities of points. both the simulations and real experimental results demonstrate the feasibility and effectiveness of the proposed algorithm. © 2016 songmin jia et al.
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آدرس
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college of electronic and control engineering,beijing university of technology,beijing,china,beijing key laboratory of computational intelligence and intelligent system,beijing,china,engineering research center of digital community,ministry of education,beijing, China, college of electronic and control engineering,beijing university of technology,beijing,china,beijing key laboratory of computational intelligence and intelligent system,beijing,china,engineering research center of digital community,ministry of education,beijing, China, college of electronic and control engineering,beijing university of technology,beijing,china,beijing key laboratory of computational intelligence and intelligent system,beijing,china,engineering research center of digital community,ministry of education,beijing, China, college of electronic and control engineering,beijing university of technology,beijing,china,beijing key laboratory of computational intelligence and intelligent system,beijing,china,engineering research center of digital community,ministry of education,beijing,china,school of mechanical and electrical engineering,henan institute of science and technology,xinxiang, China
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Authors
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