scholarly journals Mobile Sensor Networks: What Can Underground Electric Transport Vehicles do in Underground Mine Monitoring?

Author(s):  
Chenxi Zhao ◽  
Haoxuan Yu

According to our previous work, we have found that the ZigBee WSN technology and sensors are actually suitable for the underground monitoring, but there are still many problems. So in this viewpoint paper, we showed our viewpoint that the underground driver-less electric transport vehicles could also play an important role in the underground monitoring, that is, underground electric transport vehicles running in the mine roadway could carry mobile sensors to monitor the environmental conditions in the transport roadway. If it could be realized, it will save the number of sensors installed around the mine so as to reduce costs. If it could be realized, the monitoring of underground mines will become more convenient.

2014 ◽  
Vol 02 (03) ◽  
pp. 243-248 ◽  
Author(s):  
Cheng Song ◽  
Gang Feng

This paper investigates the coverage problem for mobile sensor networks on a circle. The goal is to minimize the largest distance from any point on the circle to its nearest sensor while preserving the mobile sensors' order. The coverage problem is translated into a multi-agent consensus problem by showing that the largest distance from any point to its nearest sensor is minimized if the counterclockwise distance between each sensor and its right neighbor reaches a consensus. Distributed control laws are also developed to drive the mobile agents to the optimal configuration with order preservation. Simulation results illustrate the effectiveness of the proposed control laws.


2010 ◽  
Vol 21 (3) ◽  
pp. 490-504 ◽  
Author(s):  
Fu-Long XU ◽  
Ming LIU ◽  
Hai-Gang GONG ◽  
Gui-Hai CHEN ◽  
Jian-Ping LI ◽  
...  

2012 ◽  
Vol 23 (3) ◽  
pp. 629-647 ◽  
Author(s):  
Lei WU ◽  
Xiao-Min WANG ◽  
Ming LIU ◽  
Gui-Hai CHEN ◽  
Hai-Gang GONG

Author(s):  
Jongeun Choi ◽  
Dejan Milutinović

This tutorial paper presents the expositions of stochastic optimal feedback control theory and Bayesian spatiotemporal models in the context of robotics applications. The presented material is self-contained so that readers can grasp the most important concepts and acquire knowledge needed to jump-start their research. To facilitate this, we provide a series of educational examples from robotics and mobile sensor networks.


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