[1]伍明,李琳琳,李承剑.基于协方差交集的多机器人协作目标跟踪算法[J].智能系统学报,2013,8(1):66-73.[doi:10.3969/j.issn.1673-4785.201204022]
WU Ming,LI Linlin,LI Chengjian.An algorithm of multi robot cooperative object tracking based on covariance intersection[J].CAAI Transactions on Intelligent Systems,2013,8(1):66-73.[doi:10.3969/j.issn.1673-4785.201204022]
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《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
8
期数:
2013年第1期
页码:
66-73
栏目:
学术论文—智能系统
出版日期:
2013-03-25
- Title:
-
An algorithm of multi robot cooperative object tracking based on covariance intersection
- 文章编号:
-
1673-4785(2013)01-0066-08
- 作者:
-
伍明,李琳琳,李承剑
-
第二炮兵工程大学 指挥信息工程系,陕西 西安 710025
- Author(s):
-
WU Ming, LI Linlin, LI Chengjian
-
Command Information Engineering Department, The Second Artillery Engineering College, Xi′an 710025, China
-
- 关键词:
-
机器人; 多机器人协作; 目标跟踪算法; 协方差交集
- Keywords:
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robots; multi robot cooperation; object tracking algorithm; covariance intersection
- 分类号:
-
TP242.6
- DOI:
-
10.3969/j.issn.1673-4785.201204022
- 文献标志码:
-
A
- 摘要:
-
为了解决未知环境下多机器人协作目标跟踪问题,设计了一种基于协方差交集数据融合的分布式解决算法.单台机器人运用全协方差扩展式卡尔曼滤波器完成未知环境下机器人状态和目标状态的同步估计,当单台机器人发现同伴并利用观测值对同伴机器人状态进行本地估计后,将结果连同目标状态一起发往同伴机器人,同伴机器人进行数据验证后,采用基于协方差交集的数据融合算法完成本地相关状态的更新,由于并不需要知道相关估计对象之间的协方差阵,因此算法具有分布式特点.仿真实验证明了算法能够有效提高机器人对于自身状态、环境特征状态以及目标状态的估计准确性.
- Abstract:
-
In order to solve the problem of multirobot cooperative object tracking in unknown environments, a distributed algorithm based on covariance intersection data fusion was proposed in this paper. To the single robot, states of robot and object in an unknown environment are simultaneously estimated using a full covariance extended Kalman filter. As the robot finds a partner, it will estimate the state of the partner according to observation and then send the state collectively with object state to the partner. Once the partner verifies the incoming information, the relevant local state is updated using data fusion algorithm based on a covariance intersection. Since the covariance between different states is not needed, and therefore the algorithm was distributed. The improvement in estimation precision of the robot state, environment characteristic state and object state using this approach was verified through the simulation results.
更新日期/Last Update:
2013-04-12