计算机科学与探索2017，Vol.11Issue(11)：1849-1859,11.DOI:10.3778/j.issn.1673-9418.1703052
基于改进粒子滤波的移动机器人行人跟踪
People Tracking of Mobile Robot Using Improved Particle Filter
摘要
Abstract
People tracking for mobile robot is an important application which reflects the intelligence of robot, and it has wide prospect and practical value. However, there exists a big challenge because of the complexity of environ-ment and the uncertainty of people moving. This paper improves the particle filter for mobile robot people tracking based on the analysis of particle filter framework. On the hand, the color information, depth information and social force are combined to estimate the similarity between the template and candidate, which increases the tracking preci-sion. On the other hand, a concept of secondary particle is proposed to overcome the loss of particle ' s diversity, which increases the tracking accuracy. In the last, the improved particle filter, sequential importance resampling (SIR) particle filter and extended Kalman filter (EKF) algorithm are compared on the turtlebot robot and the public data IAS-Lab. Results prove the superiority of improved particle filter.关键词
移动机器人/行人跟踪/粒子滤波/深度信息/社交力/二级粒子Key words
mobile robot/people tracking/particle filter/depth information/social force/secondary particle分类
信息技术与安全科学引用本文复制引用
夏克付,李鹏飞,陈小平..基于改进粒子滤波的移动机器人行人跟踪[J].计算机科学与探索,2017,11(11):1849-1859,11.基金项目
The Key Natural Science Research Project of Anhui Province University under Grant No. KJ2016A050 (安徽省高校自然科学研究重点项目) （安徽省高校自然科学研究重点项目）
the Fundamental Research Funds for the Central Universities of China under Grant No. WK0110000038 (中央高校基本科研业务费专项资金). （中央高校基本科研业务费专项资金）
