2025/06/09 by Melissa Jia Ying Chong, Lim, Shoon Kit, Chong, Melissa Jia Ying +4
Computer Science · Psychology · #FOS: Computer and information sciences #I.2.10 #I.2.7 #I.2.9 #Multimodal Machine Learning Applications #Robotics (cs.RO) #Social Robot Interaction and HRI #Speech and dialogue systems
paper · pdf · doi:10.48550/arxiv.2506.07509
openalex publication_date 2025/06/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recent advances in agentic and physical artificial intelligence (AI) have largely focused on ground-based platforms such as humanoid and wheeled robots, leaving aerial robots relatively underexplored. Meanwhile, state-of-the-art unmanned aerial vehicle (UAV) multimodal vision-language systems typically rely on closed-source models accessible only to well-resourced organizations. To democratize natural language control of autonomous drones, we present an open-source agentic framework that integrates PX4-based flight control, Robot Operating System 2 (ROS 2) middleware, and locally hosted models using Ollama. We evaluate performance both in simulation and on a custom quadcopter platform, benchmarking four large language model (LLM) families for command generation and three vision-language model (VLM) families for scene understanding.