Published 01-05-2024
Keywords
- Deep reinforcement learning,
- autonomous robotics,
- dentistry,
- dental robotics,
- artificial intelligence
- machine learning,
- autonomous systems,
- robotic surgery,
- dental procedures,
- sensorimotor learning ...More
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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Abstract
This paper introduces a groundbreaking application of deep reinforcement learning (DRL) in the field of dentistry, specifically focusing on autonomous robotics. Traditional robotic systems in dentistry require extensive programming and are limited in adaptability to varying conditions. In contrast, DRL enables robots to learn complex tasks through trial and error, resembling human learning. We propose a framework where a robotic system equipped with sensors and actuators learns to perform dental procedures autonomously by interacting with its environment. This approach has the potential to revolutionize dental practices by improving efficiency, accuracy, and patient outcomes. We present a comprehensive review of existing literature on DRL in robotics and discuss its implications for autonomous dental robotics. Our findings demonstrate the feasibility and benefits of applying DRL in this context, paving the way for future research and development in autonomous dental robotics.
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