Task Space Mapping for Franka Kitchen environments

[sriramsk1999]

Hello,

I am trying to set up a task-space training pipeline for the Franka Kitchen environments.

My understanding is that the input to RoboHive environments is in joint-space. In the teleop script the input to the rpFrankaRobotiqData-v0 environment is simply the normalized qpos.

This does not work for the Franka Kitchen tasks. I have a trained torchRL agent which predicts the actions, qpos and qvel. I found that the env.robot._act_mode is "vel" for the Franka Kitchen environments, so I expected that the action is the normalized qvel i.e. action = env.robot.normalize_actions(qvel).

This does not work and the robot does not move as expected. What am I doing wrong?

.

PS - This seems like a bug in the normalize_actions function. Shouldn't it be:

                        act_rng = (actuator['vel_range'][1]-actuator['vel_range'][0])/2.0

instead of

                        act_rng = (actuator['vel_range'][1]-actuator['pos_range'][0])/2.0

[sriramsk1999]

Using the qvel directly without normalizing gives close to expected results. Even then, it doesn't exactly follow the same trajectory as the predicted actions, but it comes quite close.

Related: #142

[vikashplus]

I haven't tested in cases you are using it now. This might be a good chance for me to test those. I'm traveling this week. I'll be able to take a look next week.