open access

Journal of Robotics, Automation and Smart Systems

P e e r - R e v i e w e d  
Annual (One issue per year)

Artificial Intelligence and Machine Learning

Artificial Intelligence and Machine Learning focuses on developing algorithms that enable robots and systems to learn, adapt, and perform intelligent tasks. AI and ML support pattern recognition, predictive analytics, and automation of decision-making. They enhance object detection, navigation, and robotic control through deep learning models. By analyzing massive datasets, AI systems identify trends and optimize robotic performance. These technologies power applications in industrial automation, smart systems, and autonomous platforms. With continuous advancements, AI and ML are reshaping robotics innovation and enabling smarter, more efficient operations.

 

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EDITORIAL & PUBLICATION INFORMATION

English Publication Language
Single-Blind Peer-Review Model
17% Acceptance Rate
<18% Similarity Screening Guideline
Open Access Access Model

All manuscripts undergo editorial assessment and originality screening as part of the journal's evaluation process. The acceptance rate shown is based on journal-level editorial data and may change over time. Similarity reports are assessed editorially and are not interpreted solely on the basis of a numerical similarity score.

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    • Journal Highlights

    Robotics Engineering Intelligent Automation Autonomous Systems Artificial Intelligence and Machine Learning Human-Robot Interaction Industrial Robotics Smart Manufacturing and Industry 4.0 Internet of Things -IoT Cyber-Physical Systems Computer Vision and Machine Vision UAVs and UGVs - Unmanned Aerial and Ground Vehicles Robotic Sensors and Actuators Autonomous Navigation and Path Planning Embedded and Real-Time Systems Smart Cities and Smart Infrastructure Robotics in Healthcare Agricultural and Service Robotics Robotic Manipulation and Control Edge and Cloud Robotics Safety, Ethics and Human-Centric Automation

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