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Fuzzy controller-based multisensor navigation system implemented on FPGA platform
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AI
DOI：10.1177/01423312251392771.png)
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Abstract
En 中文
Navigation is a critical component of intelligent robots and autonomous vehicles. To obtain a precise and continuous localization solution, the navigation system uses a combination of sensors including Global Positioning System (GPS), Inertial Navigation System (INS), and Odometer (Odom). Therefore, the architecture of the navigation system should provide data fusion capabilities, and account for sensor faults during navigation to make the best combination of the different sensors' information. This paper proposes a multisensor navigation system based on Fuzzy Logic Controller (FLC) that chooses the best integration scheme between GPS/INS, GPS/Odom, RISS (Reduced Inertial Sensor System), and GPS/RISS. The integration of the controller ensures an accurate navigation solution. Sensor data fusion is achieved using the Extended Kalman Filter (EKF). In our application, the proposed FLC provides a suitable decision in real-time to satisfy the navigation constraints. Therefore, the multisensor navigation system, consisting of data fusion blocks and FLC, is implemented on Field Programmable Gate Array (FPGA) platform, specifically Altera-NIOS II softcore processor. The system was evaluated in different scenarios for both accuracy and execution time. The obtained results prove that the proposed multisensor navigation system provides an accurate real-time navigation solution.
Keywords:
Navigation system
multisensor integration
Kalman filter
reduced inertial sensors system
fuzzy logic controller
FPGA
NIOS II processor
Journal
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1.9
Papers:
307
Citations:
4.2K