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Get Free AccessWireless sensor node deployment in unconstructed environments affects the network's connectivity and longevity. This paper presents the 3D self-deployment of jumping robot sensor nodes (JRSNs), which can jump over and onto obstacles to enhance network performances. The effects of JRSNs' 3D deployment on network connectivity and energy consumption are simulated first. Then, we propose a localization method by the fusion of ultra-wideband (UWB), inertial navigation system (INS), and jumping error model for JRSNs' precise locomotion during deployment. Moreover, we propose path planning and deployment algorithms considering the JRSNs' locomotion pattern and obstacles. Finally, we conducted experiments on the localization and deployment of JRSNs in an outdoor environment. The results verified the feasibility of the proposed method and algorithms. The JRSNs' deployment error was smaller than 25 cm. The network connectivity was improved significantly by 57.70% with the 3D deployment. The JRSNs can deploy autonomously for various applications in obstacle-rich environments.
Jun Zhang, Bohuai Chen, Yaning Zhang, Chaojun Jiang, Aiguo Song (2022). 3d Self-Deployment of Jumping Robot Sensor Nodes for Improving Network Performance in Obstacle Dense Environment. , DOI: https://doi.org/10.2139/ssrn.4226792.
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Type
Article
Year
2022
Authors
5
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.2139/ssrn.4226792
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