Robust Adaptive Coverage for Robotic Sensor Networks
| العنوان: | Robust Adaptive Coverage for Robotic Sensor Networks |
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| المؤلفون: | Mac Schwager, Daniela Rus, Michael P. Vitus, Claire J. Tomlin |
| المصدر: | Springer Tracts in Advanced Robotics ISBN: 9783319293622 ISRR |
| بيانات النشر: | Springer International Publishing, 2016. |
| سنة النشر: | 2016 |
| مصطلحات موضوعية: | Computer science, Bounded error, 030218 nuclear medicine & medical imaging, Weighting, 03 medical and health sciences, Light intensity, 0302 clinical medicine, Robustness (computer science), 030220 oncology & carcinogenesis, Robot, Voronoi diagram, Scalar field, Wireless sensor network, Algorithm |
| الوصف: | This paper presents a distributed control algorithm to drive a group of robots to spread out over an environment and provide adaptive sensor coverage of that environment. The robots use an on-line learning mechanism to approximate the areas in the environment which require more concentrated sensor coverage, while simultaneously exploring the environment before moving to final positions to provide this coverage. More precisely, the robots learn a scalar field, called the weighting function, representing the relative importance of different regions in the environment, and use a Traveling Salesperson based exploration method, followed by a Voronoi-based coverage controller to position themselves for sensing over the environment. The algorithm differs from previous approaches in that provable robustness is emphasized in the representation of the weighting function. It is proved that the robots approximate the weighting function with a known bounded error, and that they converge to locations that are locally optimal for sensing with respect to the approximate weighting function. Simulations using empirically measured light intensity data are presented to illustrate the performance of the method. |
| ردمك: | 978-3-319-29362-2 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::ce65a2cf1d40e8aa4e714b3a3a950183 https://doi.org/10.1007/978-3-319-29363-9_25 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........ce65a2cf1d40e8aa4e714b3a3a950183 |
| قاعدة البيانات: | OpenAIRE |
| ردمك: | 9783319293622 |
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