Converting demonstration to ee does not work about maniskill HOT 5 CLOSED

Since it's a 94-dim vector, the observation mode of the environment is state mode. We recently updated a detailed description here. Please refer to the links in the wiki for the source code used to generate the observation vector in state mode.

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Hi, do the first {39, 69}-dim of the 94-dim vector that env.get_state() returns correspond to the description of env.agent.get_state() you provided a link to, or is the agent (robot) state somewhere else in the 94-dim vector? Would it be possible for you to provide documentation for env.get_state() in the same form as documentation is provided for env.agent.get_state()? If this will take time, could you please provide a pointer to the source code which specifies what each element of the 94-dim vector that self.env.get_state() returns corresponds to?

Additionally, where can I find the articulated object asset_id in the cabinet used in the OpenCabinetDrawer_1045_link_0-v0 environment?

Thanks!

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For first question, according to here (also the link in current wiki), env.agent.get_state() is the last (38, 68) dim of the 94 dim vector in state mode (with_controller_state is always set to False in state, pointcloud, and rgbd modes)

@tongzhoumu please add documentation for object articulation.

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Hi @arjung128 ,

env.get_state() does not always return 94-dim vector, it depends on the tasks. The source code is here. Note that this state is not available in ManiSkill Challenge.

If you are designing your own experiments on the ManiSkill benchmark and need to access the object state (pose, qpos, etc.), please refer to these lines.

The partnet_mobility_id of OpenCabinetDrawer_1045_link_0-v0 is 1045.

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Got it, thanks!

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