Abstract: A map database creation method is provided. The method includes: obtaining a factor set including factors; dividing a map database into levels based on the factors, and taking each interval of the last level as one sub-database; creating an initial map based on a factor value of each factor corresponding to each sub-database, and creating the sub-database as an initial map database by storing the corresponding initial map in the sub-database; finding the initial map matching a current lighting condition from the initial map database based on the current lighting condition, and taking the found initial map as a positioning map; and performing a visual positioning based on the positioning map, creating an expanded map corresponding to the current lighting condition based on the visual positioning, and creating the sub-database corresponding to the current lighting condition as an expanded map database by storing the corresponding expanded map in the sub-database.

Abstract: A map database creation method is provided. The method includes: obtaining a factor set including factors; dividing a map database into levels based on the factors, and taking each interval of the last level as one sub-database; creating an initial map based on a factor value of each factor corresponding to each sub-database, and creating the sub-database as an initial map database by storing the corresponding initial map in the sub-database; finding the initial map matching a current lighting condition from the initial map database based on the current lighting condition, and taking the found initial map as a positioning map; and performing a visual positioning based on the positioning map, creating an expanded map corresponding to the current lighting condition based on the visual positioning, and creating the sub-database corresponding to the current lighting condition as an expanded map database by storing the corresponding expanded map in the sub-database.

Abstract: A pose determination method and a robot using the same are provided. The method includes: obtaining a two-dimensional code image collected by the camera of the robot and sensor data collected by the sensor of the robot, and determining mileage information of the robot within a predetermined duration, where the sensor data includes an acceleration and an angular velocity, determining a first pose of the camera based on two-dimensional code information recognized from the two-dimensional code image and a pose estimation function, and determining a second pose of the sensor based on the sensor data; obtaining a third pose by performing a tight coupling optimization based on the first pose and the second pose; and obtaining the pose of the robot by fusing the third pose and the mileage information. In such a manner, the accuracy of determining the pose of the robot in a complex scene can be improved.