Glass Recognition and Map Optimization Method for Mobile Robot Based on Boundary Guidance

Chinese Journal of Mechanical Engineering

Original Article

Jiangbo Lan¹  Lian Duan¹  He Gao²  Yufang Wen³  Yong Tao⁴ 

[1] Large Aircraft Advanced Training Center, Beihang University, 100191, Beijing, China;Research Institute of Aero-Engine, Beihang University, 102206, Beijing, China;School of Mechanical Engineering and Automation, Beihang University, 100191, Beijing, China;School of Mechanical Engineering and Automation, Beihang University, 100191, Beijing, China;Research Institute of Aero-Engine, Beihang University, 102206, Beijing, China;

关键词: Autonomous mobile robot;    Multi-sensor fusion;    Glass recognition;    Map optimization;   

DOI  :  10.1186/s10033-023-00902-9

 received in 2022-05-24, accepted in 2023-05-29,  发布年份 2023

来源: Springer

【 摘 要 】

Current research on autonomous mobile robots focuses primarily on perceptual accuracy and autonomous performance. In commercial and domestic constructions, concrete, wood, and glass are typically used. Laser and visual mapping or planning algorithms are highly accurate in mapping wood panels and concrete walls. However, indoor and outdoor glass curtain walls may fail to perceive these transparent materials. In this study, a novel indoor glass recognition and map optimization method based on boundary guidance is proposed. First, the status of glass recognition techniques is analyzed comprehensively. Next, a glass image segmentation network based on boundary data guidance and the optimization of a planning map based on depth repair are proposed. Finally, map optimization and path-planning tests are conducted and compared using different algorithms. The results confirm the favorable adaptability of the proposed method to indoor transparent plates and glass curtain walls. Using the proposed method, the recognition accuracy of a public test set increases to 94.1%. After adding the planning map, incorrect coverage redundancies for two test scenes reduce by 59.84% and 55.7%. Herein, a glass recognition and map optimization method is proposed that offers sufficient capacity in perceiving indoor glass materials and recognizing indoor no-entry regions.

【 授权许可】

CC BY   
© The Author(s) 2023

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