pb_robot

This is a fork of Caelan's ss-pybullet with a lot of the same base functionality but a different UI. This repo is still in heavy development both in the sense of (1) reformatting the UI and (2) adding other functionality. These instructions are also skewed toward the use of the Franka Emika Panda, since thats what I'm primarily using.

Installation

The first thing is to install a few python dependencies:

$ pip install numpy pybullet recordclass networkx

Given that, we now setup a catkin workspace. While there are not known dependencies, these instructions were writen from Ubuntu 16.04 and ROS Kinetic. For this installation we will assume ROS is already installed. To create a catkin workspace (named my-workspace below):

$ mkdir my-workspace && cd my-workspace
$ catkin config --extend /opt/ros/indigo
$ catkin config -a --cmake-args -DCMAKE_BUILD_TYPE=RelWithDebInfo

Next we want to checkout code. For now, we do not use a rosinstall and wstool (although this will probably be updated in the future):

$ cd src
$ git clone https://github.com/rachelholladay/pb_robot.git

This package uses TSRs to define grasp sets and therefore we clone an additional package:

git clone https://github.com/personalrobotics/tsr.git

Given that we can build:

$ cd ..
$ catkin build

The last piece of the installation is to compile the IKFast library for the robot. For the Panda:

$ cd src/pb_robot/src/pb_robot/ikfast/franka_panda
$ python2 setup.py build

Repo Structure

Any object in a pybullet environment is a "body". We define a set of function that can operate on a body in the body class, src/pb_robot/body.py. A body may be articulated and have joints and links. If so, when the body is created, we can define joint classes and link classes, each of which have functions that operate on the joint and link objects, defined in src/pb_robot/joints.py and src/pb_robot/links.py respectively.

A robot is an articulated body. However, since there may be several specialized functions for a robot, we create a robot class that inherits from the body class. For the panda, this is defined in src/pb_robot/panda.py. Here there are robot specific definitions and functions on the robot arm and robot hand.

Originally, most of the functions were defined in a file that I've renamed og_util.py. I'm working to break the functionality up into smaller, more specific files (i.e. aabb.py and viz.py). This is still very much in development and is why there is a significant amount of legacy code lying around. Hopefully for basic use cases, whats provided in panda.py is sufficient.

Also, most of the functionality is treating PyBullet as a kinematic simulation, not considering dynamics. I'm current developing control methods and hope to add them in to the main functionality soon.

Example Usage

Below is scripts/example_panda.py to show some basic functionality:

# Launch pybullet
utils.connect(use_gui=True)
utils.disable_real_time()
utils.set_default_camera()

# Create robot object 
robot = pb_robot.panda.Panda()

# Add floor object 
objects_path = pb_robot.helper.getDirectory()
floor_file = os.path.join(objects_path, 'furniture/short_floor.urdf')
floor = pb_robot.body.createBody(floor_file)

# Example function on body object
print floor.get_transform()

# Example functions over robot arm
q = robot.arm.GetJointValues()
pose = robot.arm.ComputeFK(q)
pose[2, 3] -= 0.1
pb_robot.viz.draw_pose(pb_robot.geometry.pose_from_tform(pose), length=0.5, width=10)
newq = robot.arm.ComputeIK(pose)
if newq is not None:
    raw_input("Move to desired pose?")
    robot.arm.SetJointValues(newq)

IPython.embed()

# Close out Pybullet
utils.wait_for_user()
utils.disconnect()             

I'll soon add an example using TSRs and BiRRT for grasping a block.

Upcoming To Dos

There is a lot of development to do. Namely I'm planning on:

• Further cleaning up / breakup functionality from forked code base
• Adding more documentation (only src/pb_robot/panda.py has the level of documention I'm happy with)
• Integrating in control methods and use of dynamics (under development in scripts/controlExperiments.py)
• Adding more planners (right now its just snap and birrt) and possibly integrating OMPL
• Keeping generic items in pb_robot and breaking out robot specific items (ik function, robot models, TSRs, etc) into robot specific repos, i.e. pb_panda, pb_yumi, pb_movo, etc. As part of this any non-robot models would get moved to the object's repo.
• Further syncing the panda development with the real robot side repo I'm developing in tandem.