- git clone git@github.com:ZJU-FAST-Lab/sampling-based-path-finding.git
- cd sampling-based-path-finding/
- catkin_make
In two seperate terminals, source first, then:
- roslaunch path_finder rviz.launch
- roslaunch path_finder test_planners.launch
In Rviz panel, add a new tool "Goal3DTool", press keyboard "g" and use mouse to set goals.
LaValle, S.M. (1998). Rapidly-exploring random trees : a new tool for path planning. The annual research report.
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.
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.
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
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.
Kuffner, James J., and Steven M. LaValle. "RRT-connect: An efficient approach to single-query path planning." Proceedings 2000 ICRA.
Qureshi, Ahmed Hussain, and Yasar Ayaz. "Intelligent bidirectional rapidly-exploring random trees for optimal motion planning in complex cluttered environments." Robotics and Autonomous Systems 68 (2015): 1-11.