Andy-Leo10 / Dijkstra-Planner

Dijkstra Planner Plugin

Switch to the branch with Dijkstra Planner

cd ~/ros2_ws/src/path_planning_checkpoint
git switch project-work

Terminal 1

export MY_ROBOT=mp_400; export MAP_NAME=neo_track1
export GAZEBO_MODEL_PATH=/home/user/ros2_ws/src/neobotix_ros2/neo_simulation2/models:/home/user/ros2_ws/src:/home/user/ros2_ws/src/neobotix_ros2
ros2 launch neo_simulation2 simulation.launch.py

Terminal 2

ros2 launch neo_nav2 neo_nav2_full.launch.xml

results.dijkstra.mp4

---

For pushing branches:

git push -u origin project-work

---

Dijkstra Class

Method	Description
configure	Configures the planner. It's called when the planner is being initialized.
cleanup	Cleans up the planner. It's called when the planner is being shut down.
activate	Activates the planner. It's called when the planner is being activated.
deactivate	Deactivates the planner. It's called when the planner is being deactivated.
createPlan	Given a start and goal pose, it computes a plan (path) and returns it.
dijkstraShortestPath	Performs Dijkstra's shortest path algorithm on a costmap to find the shortest path from a start cell to a goal cell.
fromWorldToGrid	Converts world coordinates (in meters) to grid map coordinates.
fromGridToWorld	Converts grid map coordinates to world coordinates (in meters).
gridCellxyToIndex	Converts grid cell coordinates to a linear index value.
fromIndexToGridCellxy	Converts a linear index value to grid cell coordinates.
find_neighbors	Identifies neighbor nodes by inspecting the 8 adjacent nodes.
print_map	Prints the contents of a map. Useful for debugging.

Member Variable	Description
node_	Shared pointer to the lifecycle node.
costmap_ros_	Shared pointer to the ROS costmap.
tf_	Shared pointer to the TF2 buffer.
interpolation_resolution_	The resolution for interpolation.
global_frame_, name_	The global frame of the costmap and the name of the planner.
costmap_	Pointer to the values in the occupancy grid.
origin_x_, origin_y_	The x and y values of the origin of the costmap.
resolution_	The resolution of the costmap.
width_, height_	The width and height of the costmap in number of grid cells.
map_size_	The total size of the costmap in number of grid cells.
initialized_	The initialization status of the instance variables.

Algorithm

Part 1

Repeat the following while open_list is not empty:

1. Extract the node with the smallest g_cost from open_list and call it current_node
2. Mark it as visited by adding it into closed_list
3. Check if current_node is the target node, and if so, go to phase II; otherwise, continue with step 4
4. Find the neighbors of the current_node

For each node in the list of neighbors of current_node:

5. If a neighbor is inside closed_list, skip it and pick the next neighbor
6. Case I: If a neighbor is inside open_list:

• If the new g_cost value is smaller than the current g_cost value:
  • Update its g_cost
  • Update its parent node

7. Case II: If a neighbor is not inside open_list:

• Set its g_cost
• Set its parent node
• Add it to open_list

When we are done considering all neighbors of current_node, go to step 2.

Part 2

Build the path from start to end.

• Trace back from the target node to the start node, using each node's parent node.