摘要
在动态环境中的自我定位是移动机器人的一个关键问题。机器人要完成复杂的任务,首先要感知周围环境,得到机器人的位姿,才能完成后续的决策及规划。卡尔曼滤波是一种最优化回归数据处理算法,已广泛应用于机器人导航、传感器数据融合、导弹追踪。本文将卡尔曼滤波应用于足球机器人定位中。
Self-localization in the dynamic environment is the key problem of autonomous mobile robot. Robot need to apperceive environment and know its pose to accomplish complex tasks. Kalman filter is an optimal recursive data processing algorithm, widely used in robot navigation, multi-sensor data fusion and missile scouting. In this paper, we present a self-localization method based on Kalman filter for Robocup middle-size robot.
出处
《装备制造技术》
2008年第2期45-48,共4页
Equipment Manufacturing Technology
关键词
卡尔曼滤波
导航
定位
建模
Kalman filter
Navigation
Sell-localization
Modeling
