REVIEW article
Front. Robot. AI
Sec. Field Robotics
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1605405
Agentic LLM-based Robotic Systems for Real-World Applications: A Review on their Agenticness and Ethics
Provisionally accepted- 1Information Technologies Institute, Centre of Research and Technology Hellas, Thessaloniki, Greece
- 2Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi, East Macedonia and Thrace, Greece
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Agentic AI refers to autonomous systems that can perceive their environment, make decisions, and take actions to achieve goals with minimal or no human intervention.Recent advances in Large Language Models (LLMs) have opened new pathways to imbue robots with such "agentic" behaviors by leveraging the LLMs' vast knowledge and reasoning capabilities for planning and control. This survey provides the first comprehensive exploration of LLM-based robotic systems integration into agentic behaviors that have been validated in real-world applications. We systematically categorized these systems across navigation, manipulation, multi-agent, and general-purpose multi-task robots, reflecting the range of applications explored. We introduce a novel, first-of-its-kind agenticness classification that evaluates existing LLM-driven robotic works based on their degree of autonomy, goal-directed behavior, adaptability, and decision-making. Additionally, central to our contribution is an evaluation framework explicitly addressing ethical, safety, and transparency principles-including bias mitigation, fairness, robustness, safety guardrails, human oversight, explainability, auditability, and regulatory compliance. By jointly mapping the landscape of agentic capabilities and ethical safeguards, we uncover key gaps, tensions, and design trade-offs in current approaches. We believe that this work serves as both a diagnostic and a call to action: as LLM-empowered robots grow more capable, ensuring they remain comprehensible, controllable, and aligned with societal norms is not optional-it is essential.
Keywords: agentic AI, Large Language Models (LLMs), Autonomous Robots, Intelligent machines, Ethical AI, AI transparency, human-robot interaction, real-world applications
Received: 03 Apr 2025; Accepted: 03 Jun 2025.
Copyright: © 2025 Raptis, Kapoutsis and Kosmatopoulos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Emmanuel K. Raptis, Information Technologies Institute, Centre of Research and Technology Hellas, Thessaloniki, Greece
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.