MRSL Motion Primitive Library ROS

---

This repository is part of the Pitt RAS effort for IARC Mission 7. For an overview of the IARC competition as well as the team's efforts and technical approaches, check out our team website, and in particular the technical postmortem post for the project.

A ROS wrapper for Motion Primitive Library. Video of the original paper of "Search-based Motion Planning for Quadrotors using Linear Quadratic Minimum Time Control" has been uploaded at the follwing link: youtube. The package is still under maintenance, the API may change occasionally, please use git log to track the latest update.

Packages:

• motion_primitive_library: back-end for planning trajectory in various environments
• planning_ros_msgs: ROS msgs used in storing, visualizing and communicating
• planning_ros_utils: ROS utils for interfacing with MPL, it also includes mapping and rviz plugins
• mpl_test_node: examples code for simple testing

Installation

Prerequisite:

• ROS(Indigo+)
• catkin_simple
• DecompROS

If the submodule motion_primitive_library is not initialized yet, run following commands at first:

$ cd /PATH/TO/mpl_ros
$ git submodule update --init 

1) Using Catkin:

$ mv mpl_ros ~/catkin_ws/src
$ cd ~/catkin_ws & catkin_make_isolated -DCMAKE_BUILD_TYPE=Release

2) Using Catkin Tools (recommended):

$ mv mpl_ros ~/catkin_ws/src
$ catkin config -DCMAKE_BUILD_TYPE=Release
$ cd ~/catkin_ws & catkin build

Usage

Simple test using the built-in data can be run using the following commands:

$ cd ./mpl_test_node/launch/test_primitive_map
$ roslaunch rviz.launch
$ roslaunch test.launch

If it runs succesfully, you should be able to see following print out:

[ INFO] [1517950714.592547755]: Get data!
[MPPlanner] PLANNER VERBOSE ON
[MPBaseUtil] set epsilon: 1.000000
[MPBaseUtil] set v_max: 2.000000
[MPBaseUtil] set a_max: 1.000000
[MPBaseUtil] set u_max: 1.000000
[MPBaseUtil] set dt: 1.000000
[MPBaseUtil] set max num: -1
[MPBaseUtil] set tol_dis: 1.000000
[MPBaseUtil] set tol_vel: 1.000000
[MPBaseUtil] set tol_acc: 1.000000
start pos: [12.500000, 1.400000, 0.000000], vel: [1.000000, 0.000000, 0.000000], acc: [0.000000, 0.000000, 0.000000]
goal pos: [6.400000, 16.600000, 0.000000], vel: [0.000000, 0.000000, 0.000000], acc: [0.000000, 0.000000, 0.000000]
[MPBaseUtil] set effort in acc
Start from new node!
goalNode fval: 111.258702, g: 97.000000!
Expand [277] nodes!
Reached Goal !!!!!!

t: 9 --> 8
g: 97.000000, rhs: inf, h: 14.258702
t: 8 --> 7
g: 86.000000, rhs: inf, h: 21.483618
t: 7 --> 6
g: 75.000000, rhs: inf, h: 28.925053
t: 6 --> 5
g: 65.000000, rhs: inf, h: 37.819469
t: 5 --> 4
g: 54.000000, rhs: inf, h: 47.751727
t: 4 --> 3
g: 44.000000, rhs: inf, h: 53.842936
t: 3 --> 2
g: 33.000000, rhs: inf, h: 63.910897
t: 2 --> 1
g: 22.000000, rhs: inf, h: 74.000250
t: 1 --> 0
g: 11.000000, rhs: inf, h: 80.954339
[ INFO] [1517950714.627870219]: Succeed! Takes 0.008684 sec for planning, expand [277] nodes
================== Traj -- total J: 7.000000, total time: 9.000000
================ Refined traj -- total J: 5.796949, total time: 9.000000

Another example using ellipsoid model can be found in mpl_test_node/launch/test_primitive_cloud, in which a point cloud is used as obstacles, and the robot is modeled as ellipsoid. More information can be found in the paper "Search-based Motion Planning for Aggressive Flight in SE(3)".

The planned trajectory and voxel map are visualized in Rviz as:

Use Maps

The built-in maps are listed as below:

Simple	Levine	Skir	Office

User can form their own maps using the mapping_utils, a launch file example is provided in ./mpl_test_node/launch/map_generator for converting a STL file into voxel map. For details about the full utilities, please refer to wiki.