Zhenqiang Mi — accepted AI-conference papers

2024

An Object-Driven Navigation Strategy Based on Active Perception and Semantic Association

Yu Guo, Jinsheng Sun, Ruiheng Zhang, Zhiqi Jiang, Zhenqiang Mi, Chao Yao +2

RA-L 2024

Efficiently navigating to a specific kind of objects in an unknown environment is an important and challenging research topic in Embodied AI. Existing methods, such as end-to-end learning ones and modular ones still struggle at this task as they have poor efficiency, interpretability and/or generali

Cited by 5 Source ↗Scholar ↗

2023

Indoor Visual Re-Localization for Long-Term Autonomous Robots Based on Object-Level Features and Semantic Relationships

Yuanyan Xie, Yu Guo, Zhenqiang Mi, Xiaokun Wang, Yang Yang, Mohammad S. Obaidat

RA-L 2023

Visual re-localization has become one of the key technologies for long-term autonomous robots. Existing methods, mostly focusing on addressing day-night, weather, and seasonal changes, are not applicable in indoor scenarios. At the same time, the layouts of objects in indoor scenes are highly dynami

Cited by 3 Source ↗Scholar ↗