Multi-robot Exploration for Environmental Monitoring - Tiwari, Kshitij;Chong, Nak Young
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Multi-robot Exploration for Environmental Monitoring: The Resource Constrained Perspective provides readers with the necessary robotics and mathematical tools required to realize the correct architecture. The architecture discussed in the book is not confined to environment monitoring, but can also be extended to search-and-rescue, border patrolling, crowd management and related applications. Several law enforcement agencies have already started to deploy UAVs, but instead of using teleoperated UAVs this book proposes methods to fully automate surveillance missions. Similarly, several…mehr

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Produktbeschreibung
Multi-robot Exploration for Environmental Monitoring: The Resource Constrained Perspective provides readers with the necessary robotics and mathematical tools required to realize the correct architecture. The architecture discussed in the book is not confined to environment monitoring, but can also be extended to search-and-rescue, border patrolling, crowd management and related applications. Several law enforcement agencies have already started to deploy UAVs, but instead of using teleoperated UAVs this book proposes methods to fully automate surveillance missions. Similarly, several government agencies like the US-EPA can benefit from this book by automating the process.

Several challenges when deploying such models in real missions are addressed and solved, thus laying stepping stones towards realizing the architecture proposed. This book will be a great resource for graduate students in Computer Science, Computer Engineering, Robotics, Machine Learning and Mechatronics.
Autorenporträt
Kshitij Tiwari is a Postdoctoral Researcher at the Department of Electrical Engineering & Automation, School of Electrical Engineering, Aalto University, Finland. He
works with the Intelligent Robotics Group within the Department. He received the Ph.D. (2018) from the Japan Advanced Institute of Science & Technology (JAIST),
Japan. He obtained the M.Sc. in Artificial Intelligence with a special focus in Intelligent Robotics from the University of Edinburgh (2014) and the B.Engg. in Electronics & Communication from the University of Hong Kong (2013). His research interests include (but are not limited to) field robotics, applied machine learning, neuronavigation, path planning under uncertainty, and related domains.