An SoC-FPGA-Based Micro UGV with Localization and Motion Planning

Yuya Kudo, A. Takada, Yuta Ishida, T. Izumi
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引用次数: 2

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.
基于soc - fpga的微型UGV定位与运动规划
本文介绍了一种微型ugv(无人地面车辆),使用具有自定位和运动规划的SoC FPGA,为FPGA设计竞赛而开发。本次竞赛的目的是利用FPGA实现低功耗、高性能的自动驾驶所需的外部状态识别和车辆控制。我们采用赛灵思Zynq UltraScale+ MPSoC和赛灵思Artix-7自动驾驶汽车。Zynq和Artix-7分别用于需要高计算成本的处理和控制直流电机等外围设备的处理。从抽象路线规划到物理控制,自动驾驶系统是一个分层结构。在自定位层,利用粒子滤波技术融合地标观测、车轮里程计和惯性里程计进行高精度估计。在路径规划层,采用inform - rrt *对路径进行规划,在路径跟踪层,采用Pure Pursuit控制车辆对路径进行跟踪。利用fpga中的少量资源,可以构建实现自动驾驶系统的平台。我们的FPGA实现的自定位和运动规划目前正在开发中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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