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Motion Planning Demos for Roscon 2018

Using Sampling Planners & Optimization Together

Installation

The current code is tested on ROS Melodic. First clone this repository and then use the hybrid.rosinstall file to pull down the required dependencies. There are some extra dependencies outside of the catkin packages, such as python-catkin-tools and python-wstool.

# Make a ROS WS and cd into the src/ folder
git clone https://github.com/Jmeyer1292/hybrid_planning_experiments.git

# Use rosinstall to pull dependencies
wstool init .
wstool merge hybrid_planning_experiments/hybrid.rosinstall
wstool update

# Build the workspace (do it in Release or RelWithDebInfo)
catkin build --cmake-args -DCMAKE_BUILD_TYPE=Release

Running

The packages are organized into "workcells" each with its own geometry. To run the demo in workcell1:

# In terminal 1
roslaunch workcell1_support simulation.launch

# In terminal 2 (and then configure it)
rosrun rviz rviz -d src/hybrid_planning_experiments/hybrid.rviz

# In terminal 3
rosrun workcell1_demos workcell1_demo

To visualize, you can load the RVIZ config hybrid.rviz in the root of this repo.

The other demos follow suit; just replace workcell1 with workcell2 or workcell3, etc...

Demonstrations

Workcell 1 (Static robot arm & sander)

Demo 1

The robot arm takes several passes back and forth sanding the "table" in front of it. This is basic but:

  1. The tool is free to rotate around Z (and it needs to because it's so close to the robot)
  2. The paths are planned independently

Workcell 2 (Gantry robot arm & sander)

Demo 2

This demo mimics the first demo, but the robot is on a gantry now. The whole process has 8 + 1 = 9 DOF.

Workcell 3 (Static robot arm, turn table & sander)

Demo 3

In this demo, the robot is trying to run its sander along a very long part and needs to move the central turn table to make this happen.

Workcell 4 (Static robot arm, barrel & welder) *ROSCON 2018

Demo 4

In this demo, the robot wants to smoothly run its weld gun along the body of this barrel.

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Sampler + Optimizing Motion Planning Demonstrations

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