Emmanuel K. Raptis
Papers
2
Total Citations
19
H-Index
2
About
Emmanuel K. Raptis is a rising researcher at the forefront of autonomous systems and embodied AI. His work bridges the critical gap between large language models (LLMs) and real-world robotics, focusing on how to build truly "agentic" machines that perceive, decide, and act with minimal human intervention. His most-cited work, a 2025 review on *Agentic LLM-based robotic systems*, has already garnered 17 citations, establishing him as a key voice on the ethical and technical dimensions of this rapidly evolving field. Beyond language-driven agents, Raptis tackles fundamental challenges in multi-robot coordination. His 2024 study on *Improving time and energy efficiency in multi-UAV coverage operations* pioneers optimization strategies for drone swarms, specifically by intelligently positioning UAVs before missions to slash both energy consumption and mission duration. This work has immediate applications in precision agriculture, search-and-rescue, and infrastructure inspection. By combining the cognitive power of LLMs with the efficiency of swarm optimization, Raptis is helping to define the next generation of autonomous systems—robots that are not only smarter, but also more practical and responsible.
Research Focus
Key Achievements
Top Papers
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