{"ID":2825554,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.21293","arxiv_id":"2512.21293","title":"Quadrupped-Legged Robot Movement Plan Generation using Large Language Model","abstract":"Traditional control interfaces for quadruped robots often impose a high barrier to entry, requiring specialized technical knowledge for effective operation. To address this, this paper presents a novel control framework that integrates Large Language Models (LLMs) to enable intuitive, natural language-based navigation. We propose a distributed architecture where high-level instruction processing is offloaded to an external server to overcome the onboard computational constraints of the DeepRobotics Jueying Lite 3 platform. The system grounds LLM-generated plans into executable ROS navigation commands using real-time sensor fusion (LiDAR, IMU, and Odometry). Experimental validation was conducted in a structured indoor environment across four distinct scenarios, ranging from single-room tasks to complex cross-zone navigation. The results demonstrate the system's robustness, achieving an aggregate success rate of over 90\\% across all scenarios, validating the feasibility of offloaded LLM-based planning for autonomous quadruped deployment in real-world settings.","short_abstract":"Traditional control interfaces for quadruped robots often impose a high barrier to entry, requiring specialized technical knowledge for effective operation. To address this, this paper presents a novel control framework that integrates Large Language Models (LLMs) to enable intuitive, natural language-based navigation....","url_abs":"https://arxiv.org/abs/2512.21293","url_pdf":"https://arxiv.org/pdf/2512.21293v1","authors":"[\"Muhtadin\",\"Vincentius Gusti Putu A. B. M.\",\"Ahmad Zaini\",\"Mauridhi Hery Purnomo\",\"I Ketut Eddy Purnama\",\"Chastine Fatichah\"]","published":"2025-12-24T17:22:00Z","proceeding":"cs.RO","tasks":"[\"cs.RO\",\"cs.HC\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}