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Improved Closed-loop Detection Algorithm Based on Dynamic Increase or Decrease Mechanism

Aiming at the problem that the visual SLAM algorithm is easily disturbed by complex environmental factors, resulting in poor closed-loop accuracy and real-time performance. An improved closed-loop detection algorithm based on a dynamic increase or decrease mechanism is proposed. The algorithm can dynamically increase or decrease the number of words in the visual bag of words in real time according to the complexity of the scene; and optimize the selected keyframes through a double-threshold keyframe selection strategy to reduce the redundancy of keyframes, thus improving the system's real-time performance. The algorithm in this paper can achieve localization and position correction in complex environments. Test results in public datasets and real scenes demonstrate the advantages of the proposed algorithm in terms of accuracy, real-time performance, and adaptability to the environment.