回环检测是SLAM问题中最关键的一环，直接关系到最后输出位姿的准确度。

Loopback detection is the most critical part of the SLAM problem, which is directly related to the accuracy of the final output pose. During the long-term movement of the robot, the cumulative error continues to increase. When the robot returns to the previous position, new constraints can be added. The correct closed-loop information can be used to eliminate odometer errors, thereby obtaining a globally consistent map. Wrong closed loop will not only interfere with graph optimization, but also cause completely wrong graph construction results.

Loop detection is the most critical link in slam problems, which is directly related to the accuracy of the final output position. The cumulative error of the robot increases over the course of a long period of motion, adding new constraints when the robot returns to its previous position. The correct closed-loop information can be used to eliminate odometer errors, resulting in a consistent map of the world. The wrong closed loop not only interferes with the optimization of the graph, but also causes the completely wrong drawing result.

Loop detection is the most important part of slam, which is directly related to the accuracy of the final output pose. In the long-term motion process of robot, the cumulative error is increasing. When the robot returns to the previous position, new constraints can be added. The correct closed-loop information can be used to eliminate odometer error, so as to get a global consistent map. The wrong closed-loop will not only interfere with the optimization of the graph, but also result in totally wrong mapping results.