| dc.description.abstract | In this study, a particle filter used for signal processing will be designed to reduce the positional uncertainty in indoor environments where current Global Positioning Systems (GPS) are often unable to function. This study will use a wireless local area network (WLAN) composed of several access points whose signal strengths are used to compute the position of a mobile vehicle. As the vehicle begins to move forward, the change in position introduces error into the received signal, causing it deviate off course. This accumulation of error will be mitigated through the use of dynamic filtering and error estimation. A particle filter will be designed and programmed into the vehicle, decreasing the error propagation brought on by changes in position. To further decrease deviation from the instructed path, the particle filter will be modified with a feedback loop using the error for a given path orientation, which we will refer to as “path-specific error”. Using both the particle filter and path-specific error estimations, it is expected that the robot will be able to follow a given path with minimal deviation. | en |
