diff --git a/docs/source/user_guide/concepts/controllers.md b/docs/source/user_guide/concepts/controllers.md index 8c8209ad9..b48d48c3b 100644 --- a/docs/source/user_guide/concepts/controllers.md +++ b/docs/source/user_guide/concepts/controllers.md @@ -4,6 +4,8 @@ Controllers are interfaces between policies and robots. The policy outputs actio **The controller defines the action space of an task.** The robot can have separate controllers for its arm, gripper, and other components. The action space is a concatenation of the action spaces of all controllers. +Note that while `pd_ee_delta_pose` type controllers that use IK may be more sample efficient to train / learn from for RL workflows, in GPU simulation running these controllers is not that fast and may slow down RL training. + ## Terminology - fixed joint: a joint that can not be controlled. The degree of freedom (DoF) is 0. @@ -46,10 +48,10 @@ For simplicity, we use the name of the arm controller to represent each combinat - gripper_pd_joint_pos (1-dim): Note that we force two gripper fingers to have the same target position. Thus, it is like a "mimic" joint. -## Mobile Manipulator + diff --git a/docs/source/user_guide/getting_started/installation.md b/docs/source/user_guide/getting_started/installation.md index 45664600b..389c7c0ae 100644 --- a/docs/source/user_guide/getting_started/installation.md +++ b/docs/source/user_guide/getting_started/installation.md @@ -1,6 +1,6 @@ # Installation -ManiSkill is a GPU-accelerated robotics benchmark built on top of [SAPIEN](https://github.com/haosulab/sapien) designed to support a wide array of applications from robot learning, learning from demonstrations, sim2real/real2sim, and more. Follow the instructions below to get started using ManiSkill. +Installing ManiSkill is quite simple with a single pip install and potentially installing vulkan if you don't have it already. From pip (stable version):