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Online Replanning in Belief Space for Partially Observable Task and Motion Problems

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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.

  • 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-Replan
  • SS-Replan$ git lfs install
  • SS-Replan$ ./pddlstream/FastDownward/build.py release64
  • SS-Replan$ cd ss-pybullet/pybullet_tools/ikfast/franka_panda
  • SS-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
  • SS-Replan$ git submodule update --init --recursive
  • SS-Replan$ ./run_pybullet.py [-h]

IsaacSim Examples

Executed using the IssacSim 3D robot simulation environment.

Real-World Examples

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.

PDDLStream

PDDL and FastDownward

PyBullet

Publications

Videos

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.

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