Advancements in Intelligent Autonomous Robotic Systems: A Review of Artificial Intelligence Integration and Real-World Applications
Keywords:
: Autonomous robotics, artificial intelligence, machine learning, human–robot interaction, deep learning, intelligent systems, robotics applicationsAbstract
The integration of artificial intelligence (AI) into autonomous robotic systems has significantly transformed modern engineering and industrial practices. Recent advancements in machine learning, computer vision, and sensor fusion have enabled robots to perform complex tasks
with minimal human intervention. The objective of this review is to analyze the evolution, current trends, and challenges associated with intelligent autonomous robotic systems. A systematic literature review was conducted using major scientific databases, focusing
on publications from the past decade. Studies related to AI-driven robotics, including reinforcement learning, deep learning, and human robot interaction, were included. The findings indicate that intelligent robots are increasingly being deployed in sectors such as healthcare, manufacturing, agriculture, and transportation. However, issues related
to safety, scalability, ethical concerns, and real-time decision-making remain significant challenges. The review concludes that while AI powered robotics holds immense potential, further interdisciplinary research is required to address existing limitations and ensure reliable, secure, and ethical deployment in real-world environments.
How to cite this article:
Patel R, Gupta N, Mehta A, Advancements in
Intelligent Autonomous Robotic Systems: A
Review of Artificial Intelligence Integration and
Real-World Applications. J Adv Res Intel Sys Robot
2026; 8(1). 12-15.
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