Track 11
Simulators
Where most robotics actually happens in 2026. The six simulators worth learning and the patterns they share.
10 published · 0 planned · 10 lessons total
- 01→
Choosing a robotics simulator in 2026
PublishedMuJoCo, Gazebo, Isaac Sim, PyBullet, Drake, Webots — six serious simulators, six sweet spots. A decision tree and honest recommendations.
~14 min
- 02→
Gazebo / Ignition: the ROS companion
PublishedURDF import, plugins, sensors, and the headless simulation workflow for CI. The simulator that ships with ROS 2 — slower than MuJoCo, but with the deepest ROS integration in the industry.
~14 min
- 03→
MuJoCo and MJX: physics for learning
PublishedOpen-source since 2021, batched on GPU since 2022 — MuJoCo is now the RL default. Here's the XML format, the Python API, and how MJX makes it 10,000× faster.
~16 min
- 04→
PyBullet: the friendly option
PublishedZero-install, URDF-native, fastest path from 'I want to simulate a robot' to 'I'm running my first script.' The teaching tool, the prototyping tool, and the lightweight RL sim that punches above its weight.
~11 min
- 05→
NVIDIA Isaac Sim and Isaac Lab
PublishedPhotorealistic sensors, USD assets, and scaling RL training to thousands of parallel environments. The simulator the industry adopted for production-scale robot learning.
~14 min
- 06→
Drake: the MIT tool nobody uses enough
PublishedMore than a simulator — a robotics research toolkit with rigorous physics, first-class optimization, and Lagrangian formulations. The tool MIT's Underactuated Robotics course teaches with.
~12 min
- 07→
Webots: the classroom favorite
PublishedCross-platform, GUI-first, and perfect for teaching cohorts with mixed hardware. The simulator that doesn't try to be cutting-edge but consistently delivers.
~9 min
- 08→
URDF, MJCF, USD: robot description formats
PublishedThe three dialects of 'what is this robot' — what each captures, what each loses, and how to convert between them without losing your mind.
~12 min
- 09→
Writing your own sim environment (Gymnasium API)
PublishedThe interface every RL framework expects. Wrap any simulator behind reset/step/observation_space, and the entire RL ecosystem can train on it. Five-method protocol; thousands of trainers.
~11 min
- 10→
Co-simulation and hardware-in-the-loop
PublishedMixing real and simulated components — when it's brilliant and when it's a debugging trap. The patterns for testing real robots against simulated worlds, and vice versa.
~12 min