摘要
针对移动机器人长时间运动后无法自身修正累计误差以及传统EKF(Extended Kalman Filter)算法计算复杂度大的问题,提出了一种基于双向激光进行回环检测的方法,通过有效的相似度检测算法检测出真实的回环,及时修正机器人的位姿。同时使用精确稀疏滞后滤波算法相辅,利用信息矩阵的自然稀疏性来降低计算复杂度。通过实验结果分析,上述两种方法的结合可以有效地减少移动机器人行驶过程中的累计误差。
Aiming at the problem that the mobile robot can not correct the cumulative error itself and the complexity of the traditional extended Kalman filter（EKF） algorithm,this paper proposes a method based on bidirectional laser for loop closure detection. Through the effective similarity detection algorithm,it can detect the real loop and timely correct the robot position. At the same time,we use the exactly sparse delayed state filters algorithm to supplement the natural sparsity of the information matrix to reduce the computational complexity. The experimental results show that the combination of the two methods can effectively reduce the cumulative error in the process of moving the robot.
出处
《微型机与应用》
2017年第20期19-22,共4页
Microcomputer & Its Applications
