25.3 GOPS Autonomous Landing Guidance Assistant System Using Systolic Fuzzy Logic System for Urban Air Mobility (UAM) Vehicles Using FPGA

The importance of the Unmanned Aircraft Systems (UAS) has been increased significantly nowadays due to the increasing demands on affording novel urban transportation system solutions that could leverage the transportation utilization ratio specially in congested urban cities. However, the viability of deploying Urban Air Mobility (UAM) solutions in our daily life depends on many critical safety factors. One of the most pivotal key players in the UAM safety aspect is their capability for accurately landing on narrow and unplanned urban lading spots. Subsequently, processing the elevation sensory data by depending on a single array-based sensor unit has many drawbacks in case of sudden electronically failure or spontaneous obstacle shadowing effects. In this paper, we proposed a multicore systolic real-time processing unit that is capable to increase the automation requirement levels for future UAMs through adopting parallel and complex sensory fusion computer architectures for increasing the accuracy of UAM during the landing process. The novel Fuzzy Logic System (FLS) processing unit is interactively dealing with Multiple Sensor Nodes (MSN) that are both frequency spectrum and spatially separated on the bottom side of an UAM. The proposed idea is surpassing the conventional single sensor-array based-solutions for UAM landing process in terms of improving the accuracy and safety concerns. The proposed systolic FLS architecture in this paper has been designed and tested using MATLAB and VHDL to be interfaced with five Lidar Sensors and five ultrasonic sensors using the Intel Altera OpenVINO FPGA board. The proposed systolic FLS processing unit achieved a processing computational speed of about 25.3 Giga Operations per Seconds (GOPS) and only 178.12 mW as core dynamic thermal power dissipation.