Hand Position Tracking based on Optimized Consistent Extended Kalman Filter | |
Lin, Tian2,3; Wenchao, Xue1,4; Long, Cheng2,3 | |
2022 | |
会议日期 | 2022-8-15至2022-8-17 |
会议地点 | 中国合肥 |
英文摘要 | This paper proposes a hand position tracking algorithm based on optimized consistent extended Kalman filter (CEKF). By introducing the previous work of the authors and analyzing the parameter of the original CEKF algorithm, the key parameter that is negatively correlated with the degree of the estimation of uncertain dynamics is determined. Then, two metaheuristic methods, the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) are used to optimize the original CEKF algorithm. To quantify the performance of the algorithms, the root-mean-square error (RMSE) is employed as the performance index. Finally, the numerical simulation and practical experiment of the hand position tracking are carried out, and the optimized algorithm achieves 9.52% and 10.94% improvements of the performance, respectively. |
会议录出版者 | IEEE |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/48585] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
通讯作者 | Long, Cheng |
作者单位 | 1.School of Mathematical Sciences, University of Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences 3.The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences 4.The Key Laboratory of Systems and Control, National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Lin, Tian,Wenchao, Xue,Long, Cheng. Hand Position Tracking based on Optimized Consistent Extended Kalman Filter[C]. 见:. 中国合肥. 2022-8-15至2022-8-17. |
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