Replay Trajectories#

There are two control modes for replay. The physics mode replays the physics actions and the states mode replays the states, so the physics mode has greater possibilities to fail across different simulators, but the states mode is bound to succeed across different simulators.

Physics replay#

python metasim/scripts/replay_demo.py --sim=isaaclab --task=CloseBox --num_envs 4

task could also be:

  • PickCube

  • StackCube

  • CloseBox

  • BasketballInHoop

States replay#

python metasim/scripts/replay_demo.py --sim=isaaclab --task=CloseBox --num_envs 4 --object-states

task could also be:

  • CloseBox

  • BasketballInHoop

Varifies commands#

Libero#

e.g.

python metasim/scripts/replay_demo.py --sim=isaaclab --task=LiberoPickButter

Simulator:

  • isaaclab

  • mujoco

Task:

  • LiberoPickAlphabetSoup

  • LiberoPickBbqSauce

  • LiberoPickChocolatePudding

  • LiberoPickCreamCheese

  • LiberoPickMilk

  • LiberoPickOrangeJuice

  • LiberoPickSaladDressing

  • LiberoPickTomatoSauce

Humanoid#

e.g.

python metasim/scripts/replay_demo.py --sim=isaaclab --num_envs=1 --robot=h1 --task=Stand --object-states

python metasim/scripts/replay_demo.py --sim=mujoco --num_envs=1 --robot=h1 --task=Stand --object-states

Simulator:

  • isaaclab

  • mujoco

Task:

  • Stand

  • Walk

  • Run

Note:

  • MuJoCo replay supports only one environment at a time, aka num_envs should be 1 (but training supports multiple environments).