Autonomous Navigation of Mobile Robots: A Fusion of Behaviour-based Robotics and Reinforcement Learning

 
9783659198083: Autonomous Navigation of Mobile Robots: A Fusion of Behaviour-based Robotics and Reinforcement Learning

Mobile robots are being popular due to their extensive application in different hazardous/ unapproachable areas, such as outer space, underwater explorations, underground coal mines monitoring, inspection in chemical/toxic/ nuclear factories etc. The conventional/ classical robotics may not serve the purpose well if these environments are totally unknown/unpredictable (even the programmer cannot imagine it). In such cases robot learning may be the best option. Learning from the past experiences, is one such way for real time application of robots for completely unknown environments. Reinforcement learning is one of the best learning methods for robots using a constant system-environment interaction. Both single and multi-agent concepts are available for implementation of learning. The current research work describes a multi-agent based reinforcement learning using the concept of behaviour-based robotics for autonomous exploration of mobile robots.

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About the Author:

Dip Narayan Ray is working in the field of Behaviour based robotics, Machine Learning (especially Reinforcement Learning) at CSIR – CMERI, Durgapur. Dr. Ray has obtained his Bachelor degree in Mechanical Engineering from NIT, Durgapur and completed his PhD in Mobile Robot navigation fusing Behaviour-based Robotics and Reinforcement Learning.

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Book Description Book Condition: New. Publisher/Verlag: LAP Lambert Academic Publishing | A Fusion of Behaviour-based Robotics and Reinforcement Learning | Mobile robots are being popular due to their extensive application in different hazardous/ unapproachable areas, such as outer space, underwater explorations, underground coal mines monitoring, inspection in chemical/toxic/ nuclear factories etc. The conventional/ classical robotics may not serve the purpose well if these environments are totally unknown/unpredictable (even the programmer cannot imagine it). In such cases robot learning may be the best option. Learning from the past experiences, is one such way for real time application of robots for completely unknown environments. Reinforcement learning is one of the best learning methods for robots using a constant system-environment interaction. Both single and multi-agent concepts are available for implementation of learning. The current research work describes a multi-agent based reinforcement learning using the concept of behaviour-based robotics for autonomous exploration of mobile robots. | Format: Paperback | Language/Sprache: english | 377 gr | 272 pp. Bookseller Inventory # K9783659198083

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Book Description LAP Lambert Academic Publishing Aug 2012, 2012. Taschenbuch. Book Condition: Neu. Neuware - Mobile robots are being popular due to their extensive application in different hazardous/ unapproachable areas, such as outer space, underwater explorations, underground coal mines monitoring, inspection in chemical/toxic/ nuclear factories etc. The conventional/ classical robotics may not serve the purpose well if these environments are totally unknown/unpredictable (even the programmer cannot imagine it). In such cases robot learning may be the best option. Learning from the past experiences, is one such way for real time application of robots for completely unknown environments. Reinforcement learning is one of the best learning methods for robots using a constant system-environment interaction. Both single and multi-agent concepts are available for implementation of learning. The current research work describes a multi-agent based reinforcement learning using the concept of behaviour-based robotics for autonomous exploration of mobile robots. 272 pp. Englisch. Bookseller Inventory # 9783659198083

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Book Description LAP Lambert Academic Publishing Aug 2012, 2012. Taschenbuch. Book Condition: Neu. Neuware - Mobile robots are being popular due to their extensive application in different hazardous/ unapproachable areas, such as outer space, underwater explorations, underground coal mines monitoring, inspection in chemical/toxic/ nuclear factories etc. The conventional/ classical robotics may not serve the purpose well if these environments are totally unknown/unpredictable (even the programmer cannot imagine it). In such cases robot learning may be the best option. Learning from the past experiences, is one such way for real time application of robots for completely unknown environments. Reinforcement learning is one of the best learning methods for robots using a constant system-environment interaction. Both single and multi-agent concepts are available for implementation of learning. The current research work describes a multi-agent based reinforcement learning using the concept of behaviour-based robotics for autonomous exploration of mobile robots. 272 pp. Englisch. Bookseller Inventory # 9783659198083

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Book Description LAP Lambert Academic Publishing Aug 2012, 2012. Taschenbuch. Book Condition: Neu. This item is printed on demand - Print on Demand Neuware - Mobile robots are being popular due to their extensive application in different hazardous/ unapproachable areas, such as outer space, underwater explorations, underground coal mines monitoring, inspection in chemical/toxic/ nuclear factories etc. The conventional/ classical robotics may not serve the purpose well if these environments are totally unknown/unpredictable (even the programmer cannot imagine it). In such cases robot learning may be the best option. Learning from the past experiences, is one such way for real time application of robots for completely unknown environments. Reinforcement learning is one of the best learning methods for robots using a constant system-environment interaction. Both single and multi-agent concepts are available for implementation of learning. The current research work describes a multi-agent based reinforcement learning using the concept of behaviour-based robotics for autonomous exploration of mobile robots. 272 pp. Englisch. Bookseller Inventory # 9783659198083

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Book Description LAP Lambert Academic Publishing, Germany, 2012. Paperback. Book Condition: New. Aufl.. Language: English . Brand New Book ***** Print on Demand *****.Mobile robots are being popular due to their extensive application in different hazardous/ unapproachable areas, such as outer space, underwater explorations, underground coal mines monitoring, inspection in chemical/toxic/ nuclear factories etc. The conventional/ classical robotics may not serve the purpose well if these environments are totally unknown/unpredictable (even the programmer cannot imagine it). In such cases robot learning may be the best option. Learning from the past experiences, is one such way for real time application of robots for completely unknown environments. Reinforcement learning is one of the best learning methods for robots using a constant system-environment interaction. Both single and multi-agent concepts are available for implementation of learning. The current research work describes a multi-agent based reinforcement learning using the concept of behaviour-based robotics for autonomous exploration of mobile robots. Bookseller Inventory # AAV9783659198083

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