Name
Abstract | ||
|---|---|---|
This paper presents a micro UGVs (Unmanned Ground Vehicles) using an SoC FPGA with self-localization and motion planning developed for the FPGA Design Competition. The purpose of this competition is to achieve external state recognition and vehicle control required for automatic driving with low power consumption and high performance using an FPGA. We adopt Xilinx Zynq UltraScale+ MPSoC and Xilinx Artix-7 for autonomous vehicles. The Zynq and Artix-7 are used for processing that requires high computational costs and processing that controls peripherals such as DC motors, respectively. An autonomous driving system is constructed with a layer structure from abstracted route planning to physical controlling. In the self-localization layer, high-precision estimation is performed by sensor fusion of landmark observations, wheel odometry, and inertial odometry using particle filter. In the path planning layer, a path is planned by Informed-RRT*, and in the path tracking layer, the vehicle is controlled to track the path by Pure Pursuit. A platform for implementing the autonomous driving system can be built with small amount of resources in the FPGAs. Our FPGA implementation of self-localization and motion planning are currently under development. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICFPT47387.2019.00095 | 2019 International Conference on Field-Programmable Technology (ICFPT) |
Keywords | Field | DocType |
SoC FPGA, Autonomous Driving, Self Localization, Motion Planning, Particle Filter, Informed-RRT* | Motion planning,Computer science,Particle filter,Odometry,Field-programmable gate array,Real-time computing,DC motor,Sensor fusion,Landmark,MPSoC | Conference |
ISBN | Citations | PageRank |
978-1-7281-2944-0 | 0 | 0.34 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuya Kudo | 1 | 0 | 0.34 |
| Atsushi Takada | 2 | 0 | 0.34 |
| Yuta Ishida | 3 | 0 | 0.34 |
| Tomonori Izumi | 4 | 34 | 20.88 |