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pathFindingForDiverseEnvironments

The implementation of the A* pathfinding algorithm encompasses applications for robotic path planning in various environments, including 3D, 2.5D, and different spatial contexts.

astar.py

This file contains the pure implementation of the A* algorithm. In the context of a matrix consisting of 0s representing pathways and 1s representing obstacles, the algorithm navigates through the matrix to find the optimal path.

start = (0,0) and goal = (5,5)

astar-closest-path.py

This file contains a modified implementation of the A* algorithm. In contrast to the standard behavior where the A* algorithm returns FALSE when it cannot find a direct path to the goal, this modified version returns the path to the nearest accessible point to the goal.

start = (0,0) and goal = (9,9)

astar-2.5d.py

This file contains a modified implementation of the A* algorithm tailored for robotic applications in a 2.5D map, where the matrix values represent height information in a given area. The algorithm introduces a parameter K, representing the maximum allowable height difference between two adjacent cells. In other words, a path is considered viable between two cells if the height difference between them is less than or equal to the specified K value. This modification is specifically designed for navigating a 2.5D environment, where the algorithm adapts to the terrain's vertical variations while considering the user-defined threshold K.

start = (0,0) and goal = (4,8)

astar-3d.py

This file encapsulates an application of the A* algorithm in a three-dimensional environment. The algorithm navigates through a 3D matrix using 26 different directions and considers cells with a value of 0 as the path and cells with a value of 1 as obstacles.

start = (0,0,0) and goal = (8,8,8)