Tomato1107 / sampling-based-path-finding

C++ implementation and visualization of some sampling-based path planners

Build & Run

Build

1. git clone [e-mail]:ZJU-FAST-Lab/sampling-based-path-finding.git
2. cd sampling-based-path-finding/
3. catkin_make

Run

In two seperate terminals, source first, then:

1. roslaunch path_finder rviz.launch
2. roslaunch path_finder test_planners.launch

In Rviz panel, add a new tool "Goal3DTool", press keyboard "g" and use mouse to set goals.

RRT

LaValle, S.M. (1998). Rapidly-exploring random trees : a new tool for path planning. The annual research report.

RRT*

Original

Karaman, Sertac, and Emilio Frazzoli. “Sampling-Based Algorithms for Optimal Motion Planning.” The International Journal of Robotics Research, vol. 30, no. 7, June 2011, pp. 846–894, doi:10.1177/0278364911406761.

RRT* with informed sampling

J. D. Gammell, T. D. Barfoot and S. S. Srinivasa, "Informed Sampling for Asymptotically Optimal Path Planning," in IEEE Transactions on Robotics, vol. 34, no. 4, pp. 966-984, Aug. 2018, doi: 10.1109/TRO.2018.2830331.

RRT* with GUILD sampling

Aditya Mandalika and Rosario Scalise and Brian Hou and Sanjiban Choudhury and Siddhartha S. Srinivasa, Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning," in Arxiv, 2021, https://arxiv.org/abs/2104.05037

RRT#

Original

O. Arslan and P. Tsiotras, "Use of relaxation methods in sampling-based algorithms for optimal motion planning," 2013 IEEE International Conference on Robotics and Automation, 2013, pp. 2421-2428, doi: 10.1109/ICRA.2013.6630906.

RRT# with informed sampling

RRT# with GUILD sampling