The team led by Professor Kan Jiangming from the School of Technology at Beijing Forestry University has recently made significant advancements in their research, which has been published in IEEE Transactions on Intelligent Transportation Systems, a top-tier journal with an Impact Factor of 8.5. The paper, titled "BASL-AD SLAM: a robust deep-learning feature-based visual SLAM system with adaptive motion model," lists Han Junyu, a doctoral candidate at the School of Technology as the first author, Associate Professor Dong Ruifang as the first corresponding author, and Professor Kan Jiangming as the second corresponding author. Beijing Forestry University is the signature unit of the first author.

Visual Simultaneous Localization and Mapping (VSLAM) plays an important role in advanced driver assistance systems and autonomous driving. Feature-based VSLAM generates very promising and visually pleasant results due to its robustness and localization precision. However, traditional feature-based VSLAM systems are prone to be degraded or fail when either the environment or the motion of robots is too challenging. To handle these problems, we proposed BASL-AD SLAM. Firstly, we leveraged the robustness of deep learning and designed a binary deep learning-based descriptor to enhance the accuracy of feature detection and matching for SLAM systems in challenging environments. Meanwhile, the real-time performance of the SLAM system can be also guaranteed. Furthermore, we proposed an adaptive motion model to supply more accurate initial poses, which facilitated subsequent feature tracking and pose optimization in SLAM. The performance was validated on public datasets. Results verified that our BASL-AD SLAM can carry out robust feature matching and tracking in real-time under challenging environments, meanwhile, pose estimation accuracy was significantly improved and the proposed SLAM system showed competing robustness and accuracy compared with ORB-SLAM3.

The research received support from National Natural Science Foundation of China (62203059) and Fundamental Research Funds for the Central Universities (2021ZY72).

Paper link: https://ieeexplore.ieee.org/document/10475131

Written by Han Junyu and Dong Ruifang
Translated and edited by Song He
Reviewed by Yu Yangyang