摘要
在蒙特卡罗定位的理论基础上,对于已知全局地图下移动机器人概率定位问题,提出基于高阶共轭粒子滤波的蒙特卡罗算法,主要利用高阶共轭无迹粒子滤波器精确设计滤波器的提议分布,使移动机器人的位置状态估计达到高阶精度;同时,结合移动机器人自身的航迹推算,来验证基于高阶共轭粒子滤波的蒙特卡罗算法的有效性。
On the basis of Monte Carlo localization theory, probability of mobile robot localization problem for the known environment, CUPF-MCL algorithm, mainly using 5 order conjugate no trace Kalman Filter precision design proposal distribution of the Particle Filter, robot state estimation is made to reach 5 order accuracy;At the same time, the validity of the CUPF-MCL algorithm is verified by comparing with the dead reckoning of the robot. Compared with the PF-MCL algorithm, the superiority of the CUPF-MCL algorithm in positioning precision is verified.
作者
姜毅
唐善政
Jiang Yi;Tang Shanzheng(Shanghai Internal Combustion Engine Research Institute, Shanghai 200000, China;SAIC Commercial Vehicle Technology Center, Shanghai 200000, China)
出处
《农业装备与车辆工程》
2019年第7期50-54,共5页
Agricultural Equipment & Vehicle Engineering
关键词
粒子滤波
蒙特卡洛定位
航迹推算
无迹变换
particle filter
Monte Carlo localization
track estimation
5thCUT
