cxdcxd / simulator

A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

LGSVL Simulator: An Autonomous Vehicle Simulator

Stay Informed

Check out our blog and subscribe to our mailing list to get the latest updates.

Introduction

LG Electronics America R&D Center has developed an HDRP Unity-based multi-robot simulator for autonomous vehicle developers. We provide an out-of-the-box solution which can meet the needs of developers wishing to focus on testing their autonomous vehicle algorithms. It currently has integration with TierIV's Autoware and Baidu's Apollo 5.0 and Apollo 3.0 platforms, can generate HD maps, and can be immediately used for testing and validation of a whole system with little need for custom integrations. We hope to build a collaborative community among robotics and autonomous vehicle developers by open sourcing our efforts.

To use the simulator with Apollo, first download the simulator binary, then follow the guide on our Apollo 5.0 fork.

To use the simulator with Autoware, first download the simulator binary, then follow the guide on our Autoware fork.

For Chinese-speaking users, you can also view our latest videos here and download our simulator releases here (code: 6k91). 对于**的用户,您也可在哔哩哔哩上观看我们最新发布的视频,从百度网盘(提取码: 6k91)上下载使用我们的仿真器。

Getting Started

You can find complete and the most up-to-date guides on our documentation website.

Running the simulator with reasonable performance and frame rate (for perception related tasks) requires a high performance desktop. Below is the recommended system for running the simulator at high quality. We are currently working on performance improvements for a better experience.

Recommended system:

  • 4 GHz Quad Core CPU
  • Nvidia GTX 1080, 8GB GPU memory
  • Windows 10 64 Bit

The easiest way to get started with running the simulator is to download our latest release and run as a standalone executable.

For the latest functionality or if you want to modify the simulator for your own needs, you can checkout our source, open it as a project in Unity, and run inside the Unity Editor. Otherwise, you can build the Unity project into a standalone executable.

Currently, running the simulator in Windows yields better performance than running on Linux.

Downloading and starting simulator

  1. Download the latest release of the LGSVL Simulator for your supported operating system (Windows or Linux) here: https://github.com/lgsvl/simulator/releases/latest
  2. Unzip the downloaded folder and run the executable.

Building and running from source

NOTE: to clone repository faster, clone only single branch:

git clone --single-branch https://github.com/lgsvl/simulator.git

Check out our instructions for getting started with building from source here.

Simulator Instructions

  1. After starting the simulator, you should see a button to open the UI in the browser.
  2. Go to the Simulations tab and select the appropriate map and vehicle. For a standard setup, select "BorregasAve" for map and "Jaguar2015XE (Apollo 5.0)" for vehicle. Click "Run" to begin.
  3. The vehicle/robot should spawn inside the map environment that was selected. Read here for an explanation of all current keyboard shortcuts and controls.
  4. Follow the guides on our respective Autoware and Apollo 5.0 repositories for instructions on running the platforms with the simulator.

Guide to simulator functionality

Look here for a guide to currently available functionality and keyboard shortcuts for using the simulator.

Contact

Please feel free to provide feedback or ask questions by creating a Github issue. For inquiries about collaboration, please email us at contact@lgsvlsimulator.com.

Copyright and License

Copyright (c) 2019 LG Electronics, Inc.

This software contains code licensed as described in LICENSE.

About

A ROS/ROS2 Multi-robot Simulator for Autonomous Vehicles

License:Other


Languages

Language:C# 85.3%Language:HLSL 9.2%Language:ShaderLab 3.6%Language:C 1.2%Language:JavaScript 0.6%Language:Shell 0.1%Language:CSS 0.1%Language:Groovy 0.1%Language:Dockerfile 0.0%Language:Batchfile 0.0%