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OPTIMIZATION ALGORITHMS FOR IMPROVING THE ACCURACY AND ROBUSTNESS OF VISUAL ODOMETRY OF GROUND-BASED MOBILE ROBOTS

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The problem of improving the accuracy and robustness of simultaneous localization and mapping methods using numerical optimization with constraints is considered. The proposed solution is based on a modification of the ORB-SLAM3 algorithm, which takes into account the peculiarities of the kinematics of ground robots and uses the complexing of visual and wheel odometry data, bundle adjustment for setting parameters that comprehensively characterize the state of the visual sensor, as well as the loop closure algorithm to correct the map. Results of the approach approbation with an OpenLoris dataset demonstrate that for several scenarios the proposed solution is significantly superior in accuracy and robustness to the ORB-SLAM3 algorithm.

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