Skip to content

Hybrid A* Path Planner for the KTH Research Concept Vehicle

License

Notifications You must be signed in to change notification settings

shike1239/path_planner

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Hybrid A* Path Planner for the KTH Research Concept Vehicle Build Status

The code in this repository is the result of my master's thesis which I have written at the Integrated Research Lab (ITRL) at KTH Royal Institute of Technology (2016). The code is documented here and the associated thesis can be found here.

The goal of the thesis and hence this code is to create a real-time path planning algorithm for the nonholonomic Research Concept Vehicle (RCV). The algorithm uses a binary obstacle map as an input, generated using LIDAR mounted on top of the vehicle. The algorithm is being developed using C++ due to real-time requirements in combination with ROS to ensure modularity and portability as well as using RViz as a visualization/simulation environment.

Key Characteristics
  • Sampling in continuous space with 72 different headings per cell (5° discretization)
  • Constrained Heuristic - nonholonomic without obstacles
  • Unconstrained Heuristic - holonomic with obstacles
  • Dubin's Shot
  • C++ real-time implementation (~10 Hz)

Large parts of the implementation are closely related to the hybrid A* algorithm developed by Dmitri Dolgov and Sebastian Thrun (Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments DOI: 10.1177/0278364909359210)

Videos
Images

Reversing in a Maze

Parking

Mitigating a U-shape Obstacle

Dependencies

Setup

Run the following command to clone, build, and launch the package (requires a sources ROS environment):

sudo apt install libompl-dev \
&& mkdir -p ~/catkin_ws/src \
&& cd ~/catkin_ws/src \
&& git clone https://github.com/karlkurzer/path_planner.git  \
&& cd .. \
&& catkin_make \
&& source devel/setup.bash \
&& rospack profile \
&& roslaunch hybrid_astar manual.launch

Visualization (Rviz)

  1. Add -> By Topic -> /map, /path, /pathVehicle, (/visualizeNode2DPoses)
  2. Click 2D Pose Estimate to set a start point on the map (p)
  3. Click 2D Nav Goal to set a goal point on the map (g)
  4. Wait for the path being searched! (this process can be visualized [optional])

Citation

In case you are using my code for your project, I would appreciate if you include a respective citation.

@mastersthesis{kurzer2016,
  author       = {Karl Kurzer}, 
  title        = {Path Planning in Unstructured Environments : A Real-time Hybrid A* Implementation for Fast and Deterministic Path Generation for the KTH Research Concept Vehicle},
  school       = {KTH Royal Institute of Technology},
  year         = 2016,
  month        = 12,
}

About

Hybrid A* Path Planner for the KTH Research Concept Vehicle

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • C++ 97.8%
  • CMake 2.2%