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MRSL Jump Point Search Planning Library

Implementation of Jump Point Search with YagSBPL. Original jump point seach algorithm is proposed in "D. Harabor and A. Grastien. Online Graph Pruning for Pathfinding on Grid Maps. In National Conference on Artificial Intelligence (AAAI), 2011". The 3D version is proposed in "S. Liu, M. Watterson, K. Mohta, K. Sun, S. Bhattacharya, C.J. Taylor and V. Kumar. Planning Dynamically Feasible Trajectories for Quadrotors using Safe Flight Corridors in 3-D Complex Environments. ICRA 2017".

Compilation

Required:

  • Boost
  • Eigen
  • yaml-cpp (Reading data files)
  • VTK (For visualizing output)

A) Simple cmake

$ mkdir build && cd build && cmake .. && make

B) Using CATKIN with ROS

$ mv jps3d ~/catkin_ws/src
$ cd ~/catkin_ws & catkin_make -DCMAKE_BUILD_TYPE=Release

Note that in other repository, add following command in CMakeLists.txt in order to correctly find jps3d:

include_directories(${JPS3D_INCLUDE_DIRS})

Example Usage

The simple API are provided in the base planner class, here are some important functions to set up a planning thread:

std::unique_ptr<PlannerBase> planner(new XXXUtil(false)); // Declare a XXX planner
planner->setMapUtil(MAP_UTIL_PTR); // Set collision checking function
bool valid = planner->plan(start, goal); // Plan from start to goal

In this library, we consider 3D voxel grid but user can write their own 2D map util plugin using the MapBaseUtil class. Three planners are provided as follows:

  • AStarUtil
  • JPS2DUtil
  • JPS3DUtil

The results from AStarUtil and JPS2DUtil are plotted in corridor.jpg. Visualization

$ ./build/test_planner_2d ../data/corridor.yaml
JPS Planner takes: 73.000000 ms
JPS Path Distance: 35.192388
AStar Planner takes: 317.000000 ms
AStar Path Distance: 35.192388

Doxygen

For more details, please refer to https://sikang.github.io/jps3d/index.html