SOURCE-LINKED INTELLIGENCE
Spatial and Semantic Reasoning for LLM-Driven Robot Navigation via MCP
Large language models (LLMs) are increasingly used as natural-language interfaces for robotic systems, yet their integration with Robot Operating System (ROS)-based navigation remains limited by two gaps. First, navigation data such as occupancy grids are represented as raw geometric messages that are difficult for LLMs to use directly as spatial or semantic context. Second, adding LLM-driven capabilities often requires custom wrappers or robot-specific interfaces, limiting reuse across systems. To address these challenges, we propose a non-invasive framework that connects LLM reasoning with R
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-23T04:29:01.000Z
First collected: 2026-09-24T01:22:21.678Z. This is not the publication date.