ABSTRACT
Recent advances in digital electronics, microprocessors, micro-electro-mechanics, and wireless communications have enabled the deployment of large-scale sensor networks where thousands of tiny sensors are distributed over a vast field to obtain fine-grained, high-precision sensing data. Due to many attractive characteristics of sensor nodes, such as small size and low cost, sensor networks2,11,14,19,22 have been adopted by many military and civil applications, from military surveillance to smart home,23 from formidable remote environment monitoring to in-plant robotic control and guidance, from data collection on other planets to guarding the agricultural field.1 Due to the limited sensing range of the sensor nodes, deploying
sensors appropriately to reach an adequate coverage level is critical for the successful completion of the issued sensing tasks.8,24
Sensor deployment has received considerable attention recently. Most previous works8,9,16,17 assumed that the environment is sufficiently known and under control. However, when the environment is unknown or hostile (such as remote harsh fields, disaster areas, and toxic urban regions), sensor deployment cannot be performed manually. To scatter sensors by aircraft is one possible solution. However, using this technique, the actual landing position cannot be controlled due to the existence of wind and obstacles such as trees and buildings. Consequently, the coverage may be inferior to the application requirements, no matter how many sensors are dropped. Moreover, in many cases, such as during in-building toxic-leak detection,12,13
chemical sensors must be placed inside a building through the entrance. In such cases, it is necessary to make use of mobile sensors, which can move to the right place to provide the required coverage. Based on the work of Sibley et al.,21 mobile sensors have already become a reality. Their mobile sensor prototype is smaller than 0.000047 m3 at a cost of less than $150 in parts.
