Stanford Interactive Perception and Robot Learning Lab
We seek to understand the underlying principles of robust sensorimotor coordination by implementing them on robots. This is the place for our Open Source code.
- 47 followers
- Stanford
- http://iprl.stanford.edu/
Popular repositories Loading
-
-
-
sceneflownet
sceneflownet PublicMotion-based Object Segmentation based on Dense RGB-D Scene Flow
-
Concept2Robot
Concept2Robot Publicsimulations used in "Concept2Robot: Learning Manipulation Concepts from Instructions and Human Demonstrations"
Repositories
Showing 10 of 21 repositories
- contact_graspnet Public Forked from NVlabs/contact_graspnet
Efficient 6-DoF Grasp Generation in Cluttered Scenes
stanford-iprl-lab/contact_graspnet’s past year of commit activity - FrankaPanda Public Forked from manips-sai/FrankaPanda
model description and driver for the Panda arm
stanford-iprl-lab/FrankaPanda’s past year of commit activity - ScaffoldLearning Public
Simulation Environments in "Learning to Scaffold the Development of Robotic Manipulation Skills"
stanford-iprl-lab/ScaffoldLearning’s past year of commit activity - mujoco-py Public Forked from openai/mujoco-py
MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.
stanford-iprl-lab/mujoco-py’s past year of commit activity
