摘要
针对服务机器人系统环境感知问题,设计了智能服务机器人系统的多传感器信息融合模块,采用扩展卡尔曼滤波算法(EKF)实现里程计与激光雷达融合的目标跟踪定位方法,建立基于EKF的定位模型,通过EKF将激光雷达的观测信息和增量式光电解码器状态的预测信息对机器人的状态进行更新,消除增量式光电解码器定位和激光雷达存在的累计误差,排除加速度的干扰得到位置的最优估计,并通过实验验证系统模块的可靠性与稳定性。
This paper designs a multi -sensor information fusion module of the intelligent service robot system,and uses the extended Kalman filter algorithm (EKF)to realize the target tracking and locating method of the odometry and LADAR,and establishes a location model based on the EKF.The state of the robot is updated by the observation information of the LADAR and the predicted information of the state of the incremental photoelectric decoder by EKF.The optimal estimation of the position is obtained by eliminating the cumulative error of the incremental photoelectric decoder location and the existence of the laser radar,and the reliability and stability of the system module are verified by experiments.
作者
孙鹏飞
刘丽兰
高增桂
陈恩来
Sun Pengfei;Liu Lilan;Gao Zenggui;Chen Enlai
出处
《计量与测试技术》
2019年第1期1-4,9,共5页
Metrology & Measurement Technique
基金
上海市工业互联网创新发展专项(2017-GYHLW-01037)
上海市科技创新行动计划项目(17511109300)
中国博士后科学基金资助项目(2018M632077)
