6 papers
osmAG-Nav: A Hierarchical Semantic Topometric Navigation Stack for Robust Lifelong Indoor Autonomy
Yongqi Zhang, Jiajie Zhang, Chengqian Li +2
The deployment of mobile robots in large-scale, multi-floor environments demands navigation systems that achieve spatial scalability without compromising local kinematic precision.…
osmAG-LLM: Zero-Shot Open-Vocabulary Object Navigation via Semantic Maps and Large Language Models Reasoning
Fujing Xie, Sören Schwertfeger, Hermann Blum
Recent open-vocabulary robot mapping methods enrich dense geometric maps with pre-trained visual-language features, achieving a high level of detail and guiding robots to find obje…
WiFi-based Global Localization in Large-Scale Environments Leveraging Structural Priors from osmAG
Xu Ma, Jiajie Zhang, Fujing Xie +1
Global localization is essential for autonomous robotics, especially in indoor environments where the GPS signal is denied. We propose a novel WiFi-based localization framework tha…
Intelligent LiDAR Navigation: Leveraging External Information and Semantic Maps with LLM as Copilot
Fujing Xie, Jiajie Zhang, Sören Schwertfeger
Traditional robot navigation systems primarily utilize occupancy grid maps and laser-based sensing technologies, as demonstrated by the popular move_base package in ROS. Unlike rob…
Robust Lifelong Indoor LiDAR Localization using the Area Graph
Fujing Xie, Sören Schwertfeger
Lifelong indoor localization in a given map is the basis for navigation of autonomous mobile robots. In this letter, we address the problem of robust localization in cluttered indo…
Empowering Robot Path Planning with Large Language Models: osmAG Map Topology & Hierarchy Comprehension with LLMs
Fujing Xie, Sören Schwertfeger
Large Language Models (LLMs) have demonstrated great potential in robotic applications by providing essential general knowledge. Mobile robots rely on map comprehension for tasks l…