本课程由Ferbin Richard推出，历时近12小时，指导学员在Ubuntu 24.04仿真环境下从空白文件构建AMR，全面覆盖URDF建模、Gazebo差速驱动、SLAM建图、AMCL定位及Nav2导航，拒绝复制代码，强调数学推导与Debug实战，培养企业级开发能力。
原始标题：AMR From Scratch: ROS 2, SLAM and Nav2 in Simulation
本课程由 Ferbin Richard 于 2026 年 8 月推出，是一门专为希望掌握自主调试能力的 ROS 2 开发者设计的硬核机器人仿真进阶课。课程历时近 12 小时，采用“从零手写”的教学方式，指导学员在 Ubuntu 24.04 纯仿真环境下，从空白文件开始构建自主移动机器人（AMR）的 URDF 模型，全面打通 Gazebo 差速驱动、基于 robot_localization 的传感器融合、SLAM 建图、AMCL 定位以及 Nav2 行为树导航的全栈技术。
课程的最大特色在于拒绝直接复制公式与现成代码，不仅逐项白板推导运动学与导航算法的底层数学原理，还刻意保留并真实演示了开发过程中的报错与 Debug 过程，旨在培养学员构建、调优及排查企业级仓储导航系统的核心实战能力。
Published 8/2026
Created by Ferbin Richard
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English + subtitle | Duration: 122 Lectures ( 11h 55m ) | Size: 5.2 GB
Build an AMR from an empty file, map a warehouse with SLAM, and navigate it with Nav2 — all in ROS 2 and Gazebo.
What you’ll learn
⚡ Build an autonomous mobile robot from an empty file: URDF, xacro, meshes, wheels, sensors and a working diff-drive plugin in Gazebo.
⚡ Map an unseen warehouse with SLAM, then localise inside it by fusing wheel odometry, IMU and laser scans with robot_localization and AMCL.
⚡ Configure and tune the full Nav2 stack: costmaps, behaviour trees, planners, controllers and recovery behaviours, on a robot you built yourself.
⚡ Derive differential-drive kinematics, odometry and path-planning algorithms on screen, term by term, instead of copying finished equations.
Requirements
❗ A computer that can run Ubuntu 24.04. No robot hardware needed
Description
This course contains the use of artificial intelligence.
Most robotics courses hand you a finished robot.This one starts with an empty file.
Over thirteen sections, you will build a warehouse-class autonomous mobile robot from scratch usingROS 2, Gazebo, SLAM and Nav2.
You will create the robot description yourself, including its chassis, wheels, joints, safety scanners, depth camera and IMU, then spawn it inside a realistic Gazebo warehouse and make it navigate autonomously.
What You Will Build
✨ A complete URDF mobile robot
✨ Differential-drive control and kinematics
✨ Laser scanners, depth camera and IMU
✨ Odometry and sensor fusion
✨ SLAM and occupancy-grid mapping
✨ Localization
✨ Nav2 costmaps, planners and controllers
✨ Behavior Trees and recovery behaviors
✨ A complete autonomous warehouse navigation system
Real Code, Real Failures
Every command is actually run on screen.
When something breaks, you watch it fail, inspect the problem and fix it properly. The debugging is intentionally kept in the course because those failures are part of building real robotics systems.
Understand the Mathematics
The mathematics is worked through step by step rather than simply showing finished formulas.
You will understand the foundations behind
✨ Differential-drive kinematics
✨ Odometry integration
✨ Occupancy-grid mapping
✨ Localization
✨ Navigation and path planning
Final Capstone
By the end of the course, all of the pieces come together into one autonomous mobile robot capable of mapping its environment, estimating its position, planning paths, avoiding obstacles and navigating through a warehouse.
Everything runs in simulation.
You need a machine capable of running Ubuntu. You do not need a physical robot.
Who this course is for
⭐ A computer that can run Ubuntu 24.04. No robot hardware needed
⭐ ROS 2 users who can launch someone else’s navigation stack but not yet debug their own.
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