Awesome
SS-Replan
Online observation, estimatation, planning, and control for a Franka Panda Robot operating in NVIDIA SRL's simulated kitchen environment.
Installation
SS-Replan supports both Python 2 and Python 3.
<!--* `sudo apt install cmake g++ make python ros-kinetic-trac-ik`-->- Install Git LFS
$ pip install numpy scipy pybullet sklearn$ git lfs clone --branch master --recurse-submodules https://github.com/caelan/SS-Replan.git$ cd SS-ReplanSS-Replan$ git lfs installSS-Replan$ ./pddlstream/FastDownward/build.py release64SS-Replan$ cd ss-pybullet/pybullet_tools/ikfast/franka_pandaSS-Replan/ss-pybullet/pybullet_tools/ikfast/franka_panda$ ./setup.py
It's also possible to use TRAC-IK instead of IKFast; however it requires installing ROS ($ sudo apt install ros-kinetic-trac-ik).
PyBullet Examples
<!--* `SS-Replan$ git pull --recurse-submodules`-->SS-Replan$ git pullSS-Replan$ git submodule update --init --recursiveSS-Replan$ ./run_pybullet.py [-h]
<img src="https://img.youtube.com/vi/TvZqMDBZEnc/0.jpg" height="250">
<!-- -->IsaacSim Examples
Executed using the IssacSim 3D robot simulation environment.
<img src="https://img.youtube.com/vi/XSZbCp0M1rw/0.jpg" height="250">
Real-World Examples
<img src="https://img.youtube.com/vi/-Jl6GtvtWb8/0.jpg" height="250">
<!-- https://developer.nvidia.com/isaac-sdk -->Citation
Caelan R. Garrett, Chris Paxton, Tomás Lozano-Pérez, Leslie P. Kaelbling, Dieter Fox. Online Replanning in Belief Space for Partially Observable Task and Motion Problems, IEEE International Conference on Robotics and Automation (ICRA), 2020.
Publications
- Online Replanning in Belief Space for Partially Observable Task and Motion Problems
- PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning
Videos
Resources
- This repository uses PDDLStream to perform hybrid robotic planning.
- PDDLStream leverages FastDownward, a classical planner, as a discrete search subroutine.
- Common robotics primitives are implemented using PyBullet.