How to Build and Test Robot Policies Using MuJoCo Physics Simulator

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MuJoCo has emerged as a widely used physics simulator for robot learning, valued for its speed, contact accuracy, and Python bindings via mujoco and dm_control libraries. A practical tutorial published on DEV Community walks developers through setting up a robot manipulation environment using MuJoCo's XML-based scene format, MJCF, with models sourced from repositories like MuJoCo Menagerie. The guide demonstrates wrapping the simulator in a standard reset and step interface to keep policy code simulator-agnostic, and includes code for randomizing object positions to support domain randomization. It also covers enabling offscreen image rendering for policies built on imitation learning, with advice to match render resolution and camera placement to real-world hardware. The tutorial is part of a series, with the next installment set to address sim-to-real transfer consistency in greater depth.

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