fiss_planner
[RA-L 2022] FISS: A Trajectory Planning Framework using Fast Iterative Search and Sampling Strategy for Autonomous Driving
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[RA-L 2022] FISS: A Trajectory Planning Framework using Fast Iterative Search and Sampling Strategy for Autonomous Driving
Basic Info
Statistics
- Stars: 169
- Watchers: 6
- Forks: 35
- Open Issues: 1
- Releases: 0
Topics
Metadata Files
README.md
FISS Planner
[RA-L 2022] FISS: A Trajectory Planning Framework using Fast Iterative Search and Sampling Strategy for Autonomous Driving
This is an improved framework based on the framework used in frenet_optimal_planner. We utilize historical planning results as prior information in heuristics and introduce an iterative search-generate-evaluate strategy to look for the optimal trajectory candidate. Compared to the current frameworks, our method can significantly reduce the number of computationally expensive operations spent during the planning and achieve 2-6 times faster.
Our paper has been accepted by RA-L 2022 and IROS 2022.
bibtex
@article{Sun_FISS_2022,
author={Sun, Shuo and Liu, Zhiyang and Yin, Huan and Ang, Marcelo H.},
journal={IEEE Robotics and Automation Letters},
title={FISS: A Trajectory Planning Framework Using Fast Iterative Search and Sampling Strategy for Autonomous Driving},
year={2022},
volume={7},
number={4},
pages={9985-9992},
doi={10.1109/LRA.2022.3191940}
}
Video
Updates
- [14 Jul 2023] An improved new version of the method, FISS+, is now available at https://github.com/SS47816/fissplusplanner
- [19 Oct 2022] Major updates in the documentation. Now you should be able use this repo out-of-the box.
Dependencies
Our package is only based on standard ROS pkgs, with no other external dependencies:
- C++11 above
- CMake: 3.0.2 above
- Eigen (included)
- ROS Packages:
- roscpp
- rospy
- tf
- tf2_ros
- std_msgs
- nav_msgs
- geometry_msgs
- autoware_msgs
- visualization_msgs
- tf2geometrymsgs
- dynamic_reconfigure
Installation
To use this package, you will need to create a catkin_ws first. Details please see the ROS official tutorial.
```bash
locate your catkin workspace (assuming ~/catkin_ws here)
cd ~/catkin_ws/src
clone the lgsvl_utils repo so that you can use this planner with the lgsvl simulator
git clone https://github.com/SS47816/lgsvl_utils.git
clone this repo
git clone https://github.com/SS47816/fiss_planner.git
cd ..
install dependencies
rosdep install --from-paths src --ignore-src -r -y
build
catkin_make
source
source devel/setup.bash ```
Usage
- Install the LGSVL simulator by following this guide
- Set up your LGSVL simulator and launch the
lgsvl_utilsnodes by following the guide - Launch the FISS planner nodes by running:
bash
# Launch nodes
roslaunch fiss_planner fiss_planner.launch
The local planner is now waiting for the global route to be published so that it can start planning.
4. You may adjust any config parameters you like in the dynamic_reconfigure window.
5. In the RVIZ window, use the 2D Nav Goal tool to selet a reachable goal point on the road as the global goal. The global planner will immediately plan a global route for you. And you will soon see the local planner starts planning.
6. Press the green A button on your joystick to enter the autonomous mode.
7. Now you should be able to see your ego vehicle moving. Have fun!
Contribution
You are welcome contributing to the package by opening a pull-request
We are following: Google C++ Style Guide, C++ Core Guidelines, and ROS C++ Style Guide
License
Our fiss_planner ROS package is licensed under Apache License 2.0
The included Eigen Library follows its own Mozilla Public License v. 2.0
Owner
- Name: Shuo Sun
- Login: SS47816
- Kind: user
- Location: Singapore
- Company: National University of Singapore
- Website: https://www.linkedin.com/in/shuosunss/
- Repositories: 10
- Profile: https://github.com/SS47816
💻 Ph.D. Candidate & Engineer @ NUS Advanced Robotics Centre
Citation (CITATION.cff)
cff-version: 1.2.0
message: >-
If you find this software useful, please cite our work as below.
type: software
authors:
- given-names: "Shuo"
family-names: "Sun"
email: "shuo.sun@u.nus.edu"
affiliation: "Department of Mechanical Engineering, National University of Singapore"
orcid: 'https://orcid.org/0000-0002-8432-0452'
title: "FISS: A Trajectory Planning Framework using Fast Iterative Search and Sampling Strategy for Autonomous Driving"
url: "https://github.com/SS47816/fiss_planner"
version: 1.0.0
date-released: 2022-02-24
preferred-citation:
type: article
authors:
- given-names: "Shuo"
family-names: "Sun"
email: "shuo.sun@u.nus.edu"
affiliation: "Department of Mechanical Engineering, National University of Singapore"
orcid: "https://orcid.org/0000-0002-8432-0452"
- given-names: "Zhiyang"
family-names: "Liu"
email: "zhiyang@u.nus.edu"
affiliation: "Department of Mechanical Engineering, National University of Singapore"
orcid: "https://orcid.org/0000-0002-0336-0269"
- given-names: "Huan"
family-names: "Yin"
email: "eehyin@ust.hk"
affiliation: "Hong Kong University of Science and Technology"
orcid: "https://orcid.org/0000-0002-0872-8202"
- given-names: "Marcelo H."
family-names: "Ang"
email: "mpeang@nus.edu.sg"
affiliation: "Department of Mechanical Engineering, National University of Singapore"
orcid: "https://orcid.org/0000-0001-8277-6408"
doi: "10.1109/LRA.2022.3191940"
journal: "IEEE Robotics and Automation Letters"
start: 9985 # First page number
end: 9992 # Last page number
title: "FISS: A Trajectory Planning Framework using Fast Iterative Search and Sampling Strategy for Autonomous Driving"
issue: 4
volume: 7
year: 2022
GitHub Events
Total
- Issues event: 1
- Watch event: 13
- Issue comment event: 1
- Fork event: 2
Last Year
- Issues event: 1
- Watch event: 13
- Issue comment event: 1
- Fork event: 2
Committers
Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| SS47816 | s****2@g****m | 39 |
| Shuo Sun | 3****6 | 9 |
Issues and Pull Requests
Last synced: about 2 years ago
All Time
- Total issues: 6
- Total pull requests: 0
- Average time to close issues: 16 days
- Average time to close pull requests: N/A
- Total issue authors: 6
- Total pull request authors: 0
- Average comments per issue: 2.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
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