Day 0: The Orientation That Didn’t Have a Single Robot in It

2026-03-24 · Source: Machine Learning on Medium · Field: Technology & Digital — Robotics & Autonomous Systems, Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, long

Summary

Nwokolo Victor Oluebubechukwu (NEVO) joined Aurora Robotics Cohort 2 on March 23rd, 2026, documenting his journey to learn autonomous vehicles. The initial "Day 0" orientation, led by instructor Bakel Bakel, focused on a mindset reset rather than technical content, emphasizing community building and practical application. Aurora Robotics aims to bridge the theory-practice gap, cultivate indigenous talent, and position Nigeria and Africa as leaders in robotics innovation. The 8-week program, featuring two classes and one assignment per week, covers topics from Git and Linux basics to Nav2, SLAM, and autonomous navigation on a physical ROSMASTER A1 robot. The curriculum intentionally forces students to set up their own Linux environments, eschewing pre-configured Docker containers to foster genuine engineering skills. The program's technical stack includes ROS 2, Gazebo, RViz, Python 3.x, C++, Rust, Git/GitHub, VS Code, OpenCV, and Ubuntu Linux.

Key takeaway

For AI Students or Software Engineers considering robotics, understand that Aurora Robotics prioritizes hands-on environment setup over pre-configured solutions to build robust engineering skills. Your commitment to mastering Linux, Git, and ROS 2 from scratch will be crucial, as the program intentionally avoids shortcuts to prepare you for real-world challenges in autonomous systems development.

Key insights

Aurora Robotics Cohort 2 emphasizes building foundational robotics engineering skills through a challenging, self-configured learning environment.

Principles

• Consistency beats intensity.
• Collaboration over competition.
• Curiosity over perfection.

Method

The program follows a learning path from concepts/theory to maths, code/simulation, and application, with a strong emphasis on self-setup of Linux environments for real-world relevance.

In practice

• Install Ubuntu Linux for robotics development.
• Utilize Git and GitHub for version control.
• Prioritize reading documentation for problem-solving.

Topics

• Robotics Training
• ROS 2
• Autonomous Navigation
• Linux Environment Setup
• Indigenous Robotics Innovation

Code references

• aurora-robotics/workshop

Best for: AI Student, Software Engineer, Robotics Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Machine Learning on Medium.