Implementing A* Algorithm
To implement the A* algorithm for grid-based path planning, we need to follow a step-by-step process. In this lesson, we will walk through the implementation of the algorithm using Python.
First, let's import the necessary libraries:
PYTHON
1import heapq
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import heapq
def a_star_algorithm(grid, start, target):
# Create a priority queue to store the open nodes
open_nodes = []
# Create a set to store the visited nodes
visited = set()
# Create a dictionary to store the parent nodes
parents = {}
# Create a dictionary to store the g-score for each node
g_scores = {}
# Create a dictionary to store the f-score for each node
f_scores = {}
# Initialize the g-score and f-score for the start node
g_scores[start] = 0
f_scores[start] = heuristic(start, target)
# Add the start node to the priority queue
heapq.heappush(open_nodes, (f_scores[start], start))
while open_nodes:
# Remove the node with the lowest f-score from the priority queue
current = heapq.heappop(open_nodes)[1]
OUTPUT
:001 > Cmd/Ctrl-Enter to run, Cmd/Ctrl-/ to comment