Wireless Sensor Network and RFID Fusion Approach for Mobile Robot Navigation

Abstract

ere are numerous applications for mobile robots that require relatively high levels of speed and precision. For many systems, these two properties are a tradeoff, as oentimes increasing the movement speed can mean failing to detect some sensors. is research attempts to create a useful and practical system by combining a wireless sensor network with a passive radio frequency identi�cation system. e sensor network provides fast general navigation in open areas and the radio frequency identi�cation system provides precision navigation near static obstacles. By fusing the data from both systems, we are able to provide fast and accurate navigation for a mobile robot. Additionally, with WSN nodes and passive RFID tag mats, the system infrastructure can be easily installed in existing environments.

Methodical Approach to Active Node Layout Generation for Robot Navigation

“…This could be a significant drawback if not all the systems to be used in a given space in the future are robust to certain layouts. Some methods using active beacons make no attempt to estimate the robot's location implicitly, such as in [8], but rather use some rough assessment of where the robot is in order to move towards it's intended goal.…”

“…The use of a virtual potential field, as shown in [8], is a concept that has been used in various methods of mobile robot navigation. There has been much discussion of the limitations of virtual potential field navigation methods.…”

“…This too is not a concern for the basis of our model as these tight spaces would be avoided in the initial map analysis stage. Though our layouts currently handle only rooms with no parallel walls with normals pointing in opposite directions, such as "C" shaped areas, by employing the safety points presented in [8], complex situations can possibly be simplified so that the present approach is applicable.…”

“…It should be noted that the system in [8] is designed with only static environments in mind. Some systems using virtual potential fields, such as [10], also handle dynamic obstacles.…”

“…As that system requires detailed location information for not only the robot, but also that of obstacles, the cost in terms of both computation and infrastructure would be significantly larger than for the system on which our mathematical model is based. While a large number of active radio beacons would be needed for a system such as in [8], the cost of these sensors can often be less than the cost of a video camera. Additionally, the cost of RFID tags would be relatively small, as they are placed only as needed and they are inexpensive.…”