Visual-Lidar Odometry with Orientation Correction towards Millimeter-Level Localization for Indoor Construction Robots

We propose a high-precision odometry method that fuses visual-lidar odometry with orientation information estimated by ceiling line features, aiming to achieve millimeter- level localization required at construction sites. Visual-Lidar Odometry and Mapping has demonstrated top-class accuracy with an error of 50 mm in benchmarks. However, when evaluated in environments with large open walls, such as indoor construction sites with few shape and image features, the method was found to be less accurate primarily due to errors in the orientation estimation. To address this issue, we propose a method that combines the use of ceiling line features to estimate the robot’s orientation angle, thereby improving the accuracy of the odometry position estimates. We evaluated the accuracy using a real robot in an environment similar to a construction site and achieved an average error of 6.2 mm (straight-line route), 7.6 mm (rectangular route), surpassing the accuracy of conventional methods. These results confirm the effectiveness of utilizing orientation correction from ceiling line features.