【摘要】 针对室内轮式移动机器人定位传感器信息单一性与误差的随机性，提出一种基于激光雷达测量噪声自适应的扩展卡尔曼滤波算法用于轮式移动机器人的定位研究，以提高定位精度。首先，通过机器人的运动特征建立运动学模型，再采用霍夫变换将激光雷达扫描信息进行直线特征的提取；其次，以扩展卡尔曼滤波将信息进行融合；最后，计算残差信息，结合模糊推理系统得到坐标比例调节系数以及角度比例调节系数用于滤波器测量噪声的实时修正。通过实验验证了该算法的可靠性。更多还原

【Abstract】 Aiming at the singleness of information and the randomness of error of indoor wheeled mobile robot positioning sensor,an extended kalman filter algorithm based on lidar measurement noise adaptive is proposed to improve the positioning accuracy of wheeled mobile robot.Firstly,the kinematics model is established through the motion characteristics of the robot,and then the lidar scanning information is extracted by hough transform.Secondly,the information is fused by extending kalman filter.Finally,the residuals are calculated and the coordinate proportional adjustment coefficient and the angle proportional adjustment coefficient are obtained by using the fuzzy inference system to correct the measurement noise in real time.Experiments show that the algorithm can improve the positioning accuracy of wheeled mobile robot.更多还原