From 88c881d5579c9fef0a76cdd381a6bc8e0b4aced3 Mon Sep 17 00:00:00 2001 From: rudrasohan Date: Tue, 24 Oct 2017 13:00:11 +0530 Subject: [PATCH] Changed Filename from A*.py to a_star.py --- Graphs/a_star.py | 101 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 101 insertions(+) create mode 100644 Graphs/a_star.py diff --git a/Graphs/a_star.py b/Graphs/a_star.py new file mode 100644 index 000000000..2ca9476e5 --- /dev/null +++ b/Graphs/a_star.py @@ -0,0 +1,101 @@ + +grid = [[0, 1, 0, 0, 0, 0], + [0, 1, 0, 0, 0, 0],#0 are free path whereas 1's are obstacles + [0, 1, 0, 0, 0, 0], + [0, 1, 0, 0, 1, 0], + [0, 0, 0, 0, 1, 0]] + +''' +heuristic = [[9, 8, 7, 6, 5, 4], + [8, 7, 6, 5, 4, 3], + [7, 6, 5, 4, 3, 2], + [6, 5, 4, 3, 2, 1], + [5, 4, 3, 2, 1, 0]]''' + +init = [0, 0] +goal = [len(grid)-1, len(grid[0])-1] #all coordinates are given in format [y,x] +cost = 1 + +#the cost map which pushes the path closer to the goal +heuristic = [[0 for row in range(len(grid[0]))] for col in range(len(grid))] +for i in range(len(grid)): + for j in range(len(grid[0])): + heuristic[i][j] = abs(i - goal[0]) + abs(j - goal[1]) + if grid[i][j] == 1: + heuristic[i][j] = 99 #added extra penalty in the heuristic map + + +#the actions we can take +delta = [[-1, 0 ], # go up + [ 0, -1], # go left + [ 1, 0 ], # go down + [ 0, 1 ]] # go right + + +#function to search the path +def search(grid,init,goal,cost,heuristic): + + closed = [[0 for col in range(len(grid[0]))] for row in range(len(grid))]# the referrence grid + closed[init[0]][init[1]] = 1 + action = [[0 for col in range(len(grid[0]))] for row in range(len(grid))]#the action grid + + x = init[0] + y = init[1] + g = 0 + f = g + heuristic[init[0]][init[0]] + cell = [[f, g, x, y]] + + found = False # flag that is set when search is complete + resign = False # flag set if we can't find expand + + while not found and not resign: + if len(cell) == 0: + resign = True + return "FAIL" + else: + cell.sort()#to choose the least costliest action so as to move closer to the goal + cell.reverse() + next = cell.pop() + x = next[2] + y = next[3] + g = next[1] + f = next[0] + + + if x == goal[0] and y == goal[1]: + found = True + else: + for i in range(len(delta)):#to try out different valid actions + x2 = x + delta[i][0] + y2 = y + delta[i][1] + if x2 >= 0 and x2 < len(grid) and y2 >=0 and y2 < len(grid[0]): + if closed[x2][y2] == 0 and grid[x2][y2] == 0: + g2 = g + cost + f2 = g2 + heuristic[x2][y2] + cell.append([f2, g2, x2, y2]) + closed[x2][y2] = 1 + action[x2][y2] = i + invpath = [] + x = goal[0] + y = goal[1] + invpath.append([x, y])#we get the reverse path from here + while x != init[0] or y != init[1]: + x2 = x - delta[action[x][y]][0] + y2 = y - delta[action[x][y]][1] + x = x2 + y = y2 + invpath.append([x, y]) + + path = [] + for i in range(len(invpath)): + path.append(invpath[len(invpath) - 1 - i]) + print "ACTION MAP" + for i in range(len(action)): + print action[i] + + return path + +a = search(grid,init,goal,cost,heuristic) +for i in range(len(a)): + print a[i] +