📊
KerloudUAV
  • Kerloud UAV Main Page
  • 📗Kerloud UAV User Guide
    • Introduction
    • System Overview
    • Hardware Options
      • Kerloud 300
      • Kerloud 600
    • Gallery
    • Quick Start
    • Application Programming Interface (API)
    • Tutorials
      • Powering and Programming Interface
      • Offboard Control with Mavros (C++)
      • Offboard Control with Mavros (Python)
      • Indoor Positioning with Optical Flow
      • Flight Data Analysis
      • Virtual Simulation
      • Camera Pod Operation
      • Real Time Visual Recognition
      • Deep Learning in ROS
      • Enabling Autonomous Indoor Flight with a Tracking Camera
      • Hardware-in-the-loop Simulation in Airsim Environment
      • Visual Inertial System (VINS) with Stereo Vision and GPU Acceleration
      • DASA Swarm Simulation Toolbox
    • Video Instructions
  • 📘Kerloud UAV使用说明
    • 介绍
    • 系统组成
    • 硬件选项
      • Kerloud 300
      • Kerloud 600
    • 展示区
    • 快速启动
    • 应用程序接口 (API)
    • 使用教程
      • 供电和编程界面
      • Mavros在线控制 (C++)
      • Mavros在线控制 (Python)
      • 室内光流定位
      • 飞行数据分析
      • 虚拟仿真空间
      • 吊舱操作
      • 实时视觉识别
      • ROS深度学习集成
      • 基于跟踪相机的室内自主飞行实现
      • Airsim环境下的硬件在环仿真
      • 基于立体视觉和GPU加速的视觉里程系统(VINS)
      • DASA集群仿真工具箱
    • 视频指导
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  • Beginner Level
  • Intermediate Level
  • Advanced Level
  • Coming Soon

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  1. Kerloud UAV User Guide

Tutorials

PreviousApplication Programming Interface (API)NextPowering and Programming Interface

Last updated 2 years ago

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The tutorial chapter covers the following content up to now:

Beginner Level

  • : This tutorial walks you through how to setup the power connection and start programming with the Kerloud UAV series.

  • : This tutorial introduces an offboard control example (C++ language) for a waypoint mission using the mavros package.

  • : The tutorial introduces an example on how to operate Kerloud UAV with the mavros package via Python.

  • : This tutorial presents details to realize indoor positioning based on optical flow with minimum setup for Kerloud UAV.

  • : This tutorial covers procedures to analyze flight performance with onboard data logs.

Intermediate Level

  • : This tutorial provides steps to explore a virtual simulation environment for autonomous flights.

  • : This tutorial shows details on how to operate the camera pod equipped on a Kerloud 600 UAV.

  • : This tutorial guides you through how to get the Nvidia Jetson computer started for real time visual recognition with the onboard CSI camera.

  • : This tutorial introduces the details on how to integrate the deep learning capability from the Nvidia community in ROS.

  • : This tutorial describes the steps to achieve autonomous indoor flights with our Kerloud Nano VIO Indoor UAV.

Advanced Level

Coming Soon

More advanced features are coming soon for our Kerloud UAV series, and they are not limited to:

  • SLAM (Simultaneous Localization and Mapping)

  • Path planning

  • Obstacle avoidance

  • Aggressive fast flight …

So stay with us and stay tuned!

: This tutorial illustrates how to perform HIL (hardware-in-the-loop) simulation in Airsim environment with a Kerloud autopilot.

: This tutorial provides a guidance to realize a GPU-accelerated visual inertial system (VINS) by fusing stereo vision and IMU data.

: This tutorial introduces the DASA swarm simulation toolbox to facilitate the conceptualization and validation of UAV swarm algorithms.

📗
Powering and Programming Interface
Offboard Control with Mavros (C++)
Offboard Control with Mavros (Python)
Indoor Positioning with Optical Flow
Flight Data Analysis
Virtual Simulation
Camera Pod Operation
Real Time Visual Recognition
Deep Learning in ROS
Enabling Autonomous Indoor Flight with a Tracking Camera
Hardware-in-the-loop Simulation in Airsim Environment
Visual Inertial System (VINS) with Stereo Vision and GPU Acceleration
DASA Swarm Simulation Toolbox