Abstract
Navigation algorithms integrating measurements from multi-sensor systems overcome the problems that arise from using GPS navigation systems in standalone mode. Algorithms which integrate the data from 2D low-cost reduced inertial sensor system (RISS), consisting of a gyroscope and an odometer or wheel encoders, along with a GPS receiver via a Kalman filter has proved to be worthy in providing a consistent and more reliable navigation solution compared to standalone GPS receivers. It has been also shown to be beneficial, especially in GPS-denied environments such as urban canyons and tunnels. The main objective of this paper is to narrow the idea-to-implementation gap that follows the algorithm development by realizing a low-cost real-time embedded navigation system capable of computing the data-fused positioning solution. The role of the developed system is to synchronize the measurements from the three sensors, relative to the pulse per second signal generated from the GPS, after which the navigation algorithm is applied to the synchronized measurements to compute the navigation solution in real-time. Employing a customizable soft-core processor on an FPGA in the kernel of the navigation system, provided the flexibility for communicating with the various sensors and the computation capability required by the Kalman filter integration algorithm.
Highlights
Navigation is the science which comprises the methods and technologies to determine the time varying position, velocity and attitude of a moving object by utilizing either sensor-based or satellite-based measurements or by integrating the measurements from both navigation systems [1].The Global Positioning System (GPS) is a satellite-based, absolute-positioning navigation system, developed by the US Department of Defense (DoD) in the early 1970s, used to provide time, position and velocity information [2]
The logic cells used are 20% of the total available and the Block RAM (BRAM) is 33.3% of the total available, which means that a lower-density field programmable gate arrays (FPGA) can be used for implementing the system
It has to be mentioned that the host machine is not externally powered and depends on batteries which made the experiments on the mobile robot limited to a maximum of 1–1.5 hours
Summary
Navigation is the science which comprises the methods and technologies to determine the time varying position, velocity and attitude of a moving object by utilizing either sensor-based or satellite-based measurements or by integrating the measurements from both navigation systems [1]. The navigation solution that is provided by GPS is sufficiently accurate, in the order of meters to centimeters, especially when augmented with other satellite-based or ground-based augmentation systems, it is unable to fulfill the requirements of continuity and reliability in some situations. Due to the mentioned reasons, GPS can’t provide a continuous and reliable solution when used as a stand-alone navigation system, and a better navigation solution can be obtained by integrating the measurements from one or more sensor-based systems, with GPS measurements
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