[D] MuJoCo vs PyBullet? (esp. for custom environment)

1. dm_control

   1 7 4,068 8.4 Python

   Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

   

   If you're interested in using Mujoco, I'd suggest checking out the dm_control package for Python bindings rather than interfacing with C++ directly. I think one downside to Mujoco currently is that you cannot dynamically add objects, and the entire simulation is initialized and loaded according to the MJCF / XML file.

2. InfluxDB

   www.influxdata.com featured

   InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.

   

3. IsaacGymEnvs

   2 8 2,426 0.0 Python

   Isaac Gym Reinforcement Learning Environments

   

   If you already have experience in PyBullet then its probably not worth switching to Mujoco for creating custom environments. However, if you have the GPU compute for it, I'd recommend checking out Isaac Gym. GPU acceleration is great for spawning a bunch of envs for domain randomization, and it's already been used by recent research to get some great results that have previously taken a ridiculous amount of CPU compute.

Suggest a related project