Yaoqi Bao — accepted AI-conference papers

2022

Semantic-Direct Visual Odometry

Yaoqi Bao, Zhe Yang, Yun Pan, Ruohong Huan

RA-L 2022

Traditional direct SLAM methods formulate the camera pose and map estimation as minimization of the photometric error, which is tackled by the Gauss-Newton algorithm or the Levenberg-Marquardt algorithm in the optimization. However, the convexity of the photometric error only holds in a small region

Cited by 14 Source ↗Scholar ↗

2021

Utilization of Semantic Planes: Improved Localization and Dense Semantic Map for Monocular SLAM in Urban Environment

Yaoqi Bao, Yun Pan, Zhe Yang, Ruohong Huan

RA-L 2021

In this letter, we propose a novel semantic direct monocular simultaneous localization and mapping (SLAM) system that fuses the semantic information obtained by an advanced deep neural network (DNN) into direct sparse odometry with loop closure(LDSO), with the purpose of improving the localization a

Cited by 10 Source ↗Scholar ↗