Research on Laser SLAM Based on Improved Cartographer Algorithm
In order to solve the problem of large pose prediction error and long scan matching time of the Cartog-rapher algorithm in laser SLAM when IMU data is not reliable,an improved Cartographer algorithm is proposed.First,when predicting the prior pose,the linear velocity of the mobile robot is calculated by using the four data at the end of the data queue,and the rotation increment of the mobile robot is corrected by using the weighted fusion method;Sec-ondly,when using real-time correlation scanning matching to calibrate a priori pose,first use the sparse strategy to ob-tain the distribution of candidate pose rotation scores,then prune the areas whose candidate pose scores are less than the threshold,and finally calculate the translation weighted scores for the reserved candidate pose areas.The simula-tion shows that the improved Cartographer algorithm can effectively improve the position and attitude prediction effect when IMU data is not reliable,and shorten the time of real-time correlation scanning and matching on the basis of en-suring the quality of laser SLAM mapping.
Lasers simultaneous localization and mappingPose predictionWeighted fusionScan match
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