Aiming at the problems of long recovery time of global relocation in the adaptive Monte Carlo localization (AMCL)algorithm and low localization precision of mobile robot with a single sensor

a multi-sensor fusion localization method based on the improved AMCL algorithm is proposed.Firstly

the extended Kalman filter(EKF)is used to fuse the sensor data of odometry and the inertial measurement unit(IMU).Secondly

the DNA crossover idea of genetic algorithm is added to particle filter module of the AMCL algorithm.Finally

point cloud data of 2D LiDAR is used to correct the pose to complete autonomous positioning of mobile robot.The experimental results of indoor scenes show that the proposed method can meet the autonomous localization requirements of mobile robots in the known indoor environment

and the absolute localization error is controlled at about 2cm.The localization precision is improved by 16.5% compared with the traditional AMCL method and by 14.6% compared with the AMCL method combined with DNA crossover idea.It is improved by 9.5% compared with AMCL method based on EKF data.When the robot position occurs jumps

the relocalization recovery time is reduced by 89.3%

31.7% and 24.2% compared with the three methods

respectively.