Human interaction becomes an important issue in the field of mobile robotics.To achieve human-friendly navigation,the robot needs to recognize human on cluttered backgrounds,and this can be fulfilled by the detection ...Human interaction becomes an important issue in the field of mobile robotics.To achieve human-friendly navigation,the robot needs to recognize human on cluttered backgrounds,and this can be fulfilled by the detection of human legs.The detection of human legs is advantageous because it enables detecting environmental obstacles at such heights.In this paper,we compared the performance of an algorithm using a single laser range finder(LRF)proposed in Ref.[1] with that of well-known feature extraction approaches-bounding box and circle fitting proposed in Ref.[2] by using the same laser scanned image.展开更多
基金supported in part by the New Faculty Research Program 2012 of Kookmin University in Koreathe support from the Priority Research Centers Program (2012-0006680)the Korea-Belarus Joint Research Program (2012057348) through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology
基金The MKE(The Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support programsupervised by the NIPA(National ITIndustry Promotion Agency)(NIPA-2012-C1090-1221-0010)The MKE,Korea,under the Human Resources Development Program for Convergence Robot Specialists support programsu-pervised by the NIPA(NIPA-2012-H1502-12-1002)Basic Science Research Program through the NRF funded by the MEST(2011-0025980)and MEST(2012-0005487)
文摘Human interaction becomes an important issue in the field of mobile robotics.To achieve human-friendly navigation,the robot needs to recognize human on cluttered backgrounds,and this can be fulfilled by the detection of human legs.The detection of human legs is advantageous because it enables detecting environmental obstacles at such heights.In this paper,we compared the performance of an algorithm using a single laser range finder(LRF)proposed in Ref.[1] with that of well-known feature extraction approaches-bounding box and circle fitting proposed in Ref.[2] by using the same laser scanned image.
