GPS and low-cost INS integrated system are expected to become more widespread as a result of the availability of low cost inertial Micro-Electro-Mechanical Sensors (MEMS). Currently most of the integration systems are based on the differential GPS (DGPS) to ensure the navigation performance. However with the requirements of the base station, the system cost and complexity are significantly incr...

For indoor pedestrian navigation with a shoe-mounted inertial measurement unit (IMU), the zero velocity update (ZUPT) technique is implemented to constrain the sensors’ error. ZUPT uses the fact that a stance phase appears in each step at zero velocity to correct IMU errors periodically. This paper introduces three main contributions we have achieved based on ZUPT. Since correct stance phase de...

This paper describes the design, operation and performance test results of a miniature, low cost integrated GPS/inertial navigation system (INS) designed for use in UAV or UGV guidance systems. The system integrates a miniaturized commercial GPS with a low grade Micro-Electro-Mechanical (MEMS) inertial measurement unit (IMU). The MEMS IMU is a small self-contained package (< 1 cu inch) and incl...

This paper describes the design, operation, and test results of a miniature, low cost integrated GPS/inertial navigation system that uses commercial off-the-shelf Micro-Electro-Mechanical System (MEMS) accelerometers and gyroscopes. The MEMS inertial measurement unit (IMU) is packaged in a small size and provides the raw IMU data through a serial interface to a processor board where the inertia...

Robust nonlinear integrated navigation of GPS and low cost MEMS is a hot topic of research these days. A robust filter is required to cope up with the problem of unpredictable discontinuities and colored noises associated with low cost sensors. H∞ filter is previously used in Extended Kalman filter and Unscented Kalman filter frame. Unscented Kalman filter has a problem of Cholesky matrix facto...

Abstract: Pedestrian Dead Reckoning (PDR) by combining the Inertial Measurement Unit (IMU) and magnetometer is an independent navigation approach based on multiple sensors. Since the inertial component error is significantly determined by the parameters of navigation equations, the navigation precision may deteriorate with time, which is inappropriate for long-time navigation. Although the BeiD...

This work presents a low-cost robot, controlled by a Raspberry Pi, whose navigation system is based on vision. The strategy used consisted of identifying obstacles via optical flow pattern recognition. Its estimation was done using the Lucas-Kanade algorithm, which can be executed by the Raspberry Pi without harming its performance. Finally, an SVM-based classifier was used to identify patterns...

This article investigates the use of a multilayer feedforward artificial neural network into a GPS integrated low cost inertial navigation system based on MEMS sensors. The neural network is applied as an alternative of integration technique, with the purpose of providing better navigation solutions, during the lack of information in GPS outages portions of time. An input-output neural network ...