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Path Planning and Navigation for Mobile Robots in a Hybrid Sensor Network Without Prior Location Information : Pianificazione delle traiettorie e navigazione per robot mobili con un network di sensori ibridi senza precedenti informazioni, in: International Journal of Advanced Robotic Systems

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Autore Zhang, Zheng; Li, Zhenbo; Zhang, Dawei; Chen, Jiapin
Pubblicato  InTech Open Access Publisher, 2013
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Abstract In a hybrid wireless sensor network with mobile
and static nodes, which have no prior geographical
knowledge, successful navigation for mobile robots is one
of the main challenges. In this paper, we propose two
novel navigation algorithms for outdoor environments,
which permit robots to travel from one static node to
another along a planned path in the sensor field, namely
the RAC and the IMAP algorithms. Using this, the robot
can navigate without the help of a map, GPS or extra
sensor modules, only using the received signal strength
indication (RSSI) and odometry. Therefore, our
algorithms have the advantage of being cost‐effective. In
addition, a path planning algorithm to schedule mobile
robots’ travelling paths is presented, which focuses on
shorter distances and robust paths for robots by
considering the RSSI‐Distance characteristics. The
simulations and experiments conducted with an
autonomous mobile robot show the effectiveness of the
proposed algorithms in an outdoor environment.
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Articoli a Rivista
2000 ed oltre
Superordinate work
 
no fulltext found International Journal of Advanced Robotic Systems
Autore: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Pubblicato: 2004
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Documents: International Journal of Advanced Robotic Systems
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Time of publication 2013
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License

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