AI-Based Control Systems in Robotics
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| Format: | Recurso digital |
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2025
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| _version_ | 1866901565701357568 |
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| author | Pawan, Kumar Dheeraj, Kumar Rahul, Sen Tejinder Pal, Singh Sarao |
| author_facet | Pawan, Kumar Dheeraj, Kumar Rahul, Sen Tejinder Pal, Singh Sarao |
| contents | <p>This paper explores the integration of Artificial Intelligence (AI) in control systems for robotics, emphasizing its <br>importance in enhancing robot autonomy, efficiency, and adaptability. The research investigates various AI algorithms <br>such as reinforcement learning, fuzzy logic, and neural networks that have been employed to design robust and adaptive <br>control systems for robotic applications. The paper also discusses challenges in implementing AI-driven systems, the <br>potential for future development, and applications across industries, including manufacturing, healthcare, and autonomous <br>vehicles.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17828537 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI-Based Control Systems in Robotics Pawan, Kumar Dheeraj, Kumar Rahul, Sen Tejinder Pal, Singh Sarao AI, Control Systems, Robotics, Reinforcement Learning, Neural Networks <p>This paper explores the integration of Artificial Intelligence (AI) in control systems for robotics, emphasizing its <br>importance in enhancing robot autonomy, efficiency, and adaptability. The research investigates various AI algorithms <br>such as reinforcement learning, fuzzy logic, and neural networks that have been employed to design robust and adaptive <br>control systems for robotic applications. The paper also discusses challenges in implementing AI-driven systems, the <br>potential for future development, and applications across industries, including manufacturing, healthcare, and autonomous <br>vehicles.</p> |
| title | AI-Based Control Systems in Robotics |
| topic | AI, Control Systems, Robotics, Reinforcement Learning, Neural Networks |
| url | https://doi.org/10.5281/zenodo.17828537 |