Robot Localization Using Inertial and RF Sensors
A mobile robot must know its position in order to operate autonomously. The process of determining the robot's position from sensor data is termed robot localization. IMU and RF are a few of the many different types of sensors that can be used for navigation and localization purposes. When used independently, these sensors can achieve good accuracy when operating in certain conditions. By merging the results from multiple sensors, the accuracy over a wider range of conditions can be obtained. This work proposes a technique of merging heterogeneous information from inertial and RF sensors. Since sensors have errors associated with their readings, the robot's state will be represented using a probability distribution function (PDF). At each time step, this PDF will be updated based on the RF readings and then updated again based on the IMU readings. Better localization accuracy is obtained by using the RF and inertial sensors together.
School Location:USA - Ohio
Source Type:Master's Thesis
Keywords:robot localization navigation imu inertial sensors rf radio frequency particle filters grid based approach pdf probability density function calibration
Date of Publication:01/01/2008