What's the most reliable physics engine for control policy testing in a multi-robot simulation environment?

There isn’t a single universally “most reliable” physics engine for control policy testing in multi-robot simulation—it depends on whether you mean:

• numerical stability and contact fidelity
• determinism/repeatability
• speed for large-scale RL
• support for many robots / sensors / parallelization

That said, if your priority is reliable control-policy testing, the most commonly recommended choices are:

Best overall for physics fidelity

MuJoCo

• Very strong for rigid-body dynamics and contact-rich control
• Stable, fast, and widely used in robotics/control research
• Good for policy testing where realistic actuation and contact behavior matter
• Less ideal if you need huge multi-robot warehouse-style scenes with complex perception pipelines

Best for industrial-grade multi-robot simulation

NVIDIA Isaac Sim / Isaac Gym

• Strong multi-robot support and GPU acceleration
• Better suited for large-scale parallel policy training/testing
• Physics is good, but “reliability” can depend more on configuration and scene complexity than with MuJoCo
• Great if you want many robots and sensor-rich environments

Best open-source general-purpose option

Gazebo / Ignition Gazebo

• Very common in robotics
• Good ecosystem integration with ROS/ROS 2
• Physics quality depends on backend (ODE, Bullet, DART, Simbody)
• Often less stable/accurate for high-contact manipulation than MuJoCo

If you need deterministic game/simulation style physics

Bullet

• Flexible and widely used
• Good for many-body dynamics and robotics prototypes
• Generally not as accurate/stable as MuJoCo for contact-heavy control tasks

Practical recommendation

If your main goal is testing control policies:

• Single/few robots, contact-heavy manipulation: MuJoCo
• Many robots, scaling, GPU acceleration: Isaac Sim / Isaac Gym
• ROS-centric system integration: Gazebo / Ignition Gazebo

Short answer

If I had to pick one for “most reliable” control-policy testing, I’d choose MuJoCo for physics stability and contact robustness.
If your definition of reliability includes large-scale multi-robot throughput, then Isaac Sim/Gym may be the better choice.

If you want, I can also give you a decision table comparing MuJoCo, Isaac Sim, Gazebo, and Bullet for multi-robot RL/control testing.