کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10327056 | 680529 | 2010 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A novel low-cost, limited-resource approach to autonomous multi-robot exploration and mapping
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
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چکیده انگلیسی
Mobile robots are becoming more heavily used in environments where human involvement is limited, impossible, or dangerous. These robots perform some of the more laborious human tasks on Earth and throughout the solar system, simultaneously saving resources and offering automation. Higher levels of autonomy are also being sought in these applications, such as distributed exploration and mapping of unknown areas. Smaller, less expensive mobile robots are becoming more prevalent, which introduces unique challenges in terms of limited sensing accuracy and onboard computing resources. This paper presents a novel low-cost, limited-resource approach to autonomous multi-robot mapping and exploration in unstructured environments. Design and implementation details are presented, along with results from two planetary style environments. Results demonstrate that low-cost ($ 1250) mobile robots capable of simultaneous localization and mapping can be successfully constructed. The multi-robot system presented in this paper participated in the 2008 International Conference on Robotics and Automation (ICRA) Space Robotics Challenge, receiving two awards for successfully completing the 'Onto the Surface' and 'Map the Environment' events in a simulated planetary environment. This work demonstrates not only that such systems are possible, but also that this direction of research is important and needs attention.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Robotics and Autonomous Systems - Volume 58, Issue 2, 28 February 2010, Pages 186-202
Journal: Robotics and Autonomous Systems - Volume 58, Issue 2, 28 February 2010, Pages 186-202
نویسندگان
Christopher M. Gifford, Russell Webb, James Bley, Daniel Leung, Mark Calnon, Joseph Makarewicz, Bryan Banz, Arvin Agah,