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Mobile Robot Localization using Ceiling Landmark Positions and Edge Pixel Movement Vectors
진홍신,아디카리 써얌프,김성우,김형석,Chen, Hong-Xin,Adhikari, Shyam Prasad,Kim, Sung-Woo,Kim, Hyong-Suk Institute of Control 2010 제어·로봇·시스템학회 논문지 Vol.16 No.4
A new indoor mobile robot localization method is presented. Robot recognizes well designed single color landmarks on the ceiling by vision system, as reference to compute its precise position. The proposed likelihood prediction based method enables the robot to estimate its position based only on the orientation of landmark.The use of single color landmarks helps to reduce the complexity of the landmark structure and makes it easily detectable. Edge based optical flow is further used to compensate for some landmark recognition error. This technique is applicable for navigation in an unlimited sized indoor space. Prediction scheme and localization algorithm are proposed, and edge based optical flow and data fusing are presented. Experimental results show that the proposed method provides accurate estimation of the robot position with a localization error within a range of 5 cm and directional error less than 4 degrees.
Mobile Robot Localization using Ceiling Landmark Positions and Edge Pixel Movement Vectors
Hongxin Chen(진홍신),Shyam Prasad Adhikari(아디카리 써얌프),Sungwoo Kim(김성우),Hyongsuk Kim(김형석) 제어로봇시스템학회 2010 제어·로봇·시스템학회 논문지 Vol.16 No.4
A new indoor mobile robot localization method is presented. Robot recognizes well designed single color landmarks on the ceiling by vision system, as reference to compute its precise position. The proposed likelihood prediction based method enables the robot to estimate its position based only on the orientation of landmark.The use of single color landmarks helps to reduce the complexity of the landmark structure and makes it easily detectable. Edge based optical flow is further used to compensate for some landmark recognition error. This technique is applicable for navigation in an unlimited sized indoor space. Prediction scheme and localization algorithm are proposed, and edge based optical flow and data fusing are presented. Experimental results show that the proposed method provides accurate estimation of the robot position with a localization error within a range of 5 cm and directional error less than 4 degrees.