황중원 김남훈 윤정연 김창환 2024-01-20T14:33:32Z 2024-01-20T14:33:32Z 2021-09-06 2012-06 1975-6291 https://pubs.kist.re.kr/handle/201004/129182 In this paper we propose the method that detects moving objects in autonomous navigation vehicle using LRF sensor data. Object detection and tracking methods are widely used in research area like safe-driving, safe-navigation of the autonomous vehicle. The proposed method consists of three steps: data segmentation, mobility classification and object tracking. In order to make the raw LRF sensor data to be useful, Occupancy grid is generated and the raw data is segmented according to its appearance. For classifying whether the object is moving or static, trajectory patterns are analysed. As the last step, Markov chain Monte Carlo (MCMC) method is used for tracking the object. Experimental results indicate that the proposed method can accurately detect moving objects. Korean 한국로봇학회 MCMC 방법을 이용한 자율주행 차량의 보행자 탐지 및 추적방법 Pedestrian Detection and Tracking Method for Autonomous Navigation Vehicle using Markov chain Monte Carlo Algorithm Article 2 로봇학회 논문지, v.7, no.2, pp.113 - 119 로봇학회 논문지 7 2 113 119 N kci other ART001662810 Detection and Tracking of Moving Objects Markov Chain Monte Carlo(MCMC)