diff --git a/Astar-matplotlib/Astar/Astar.ipynb b/Astar-matplotlib/Astar/Astar.ipynb new file mode 100644 index 0000000000..1211319009 --- /dev/null +++ b/Astar-matplotlib/Astar/Astar.ipynb @@ -0,0 +1,170 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "A-star grid based implementation using matplotlib\n", + "matplotlib - https://matplotlib.org/\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#packages to import\n", + "from __future__ import print_function, division\n", + "import random\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.animation as animation\n", + "\n", + "\n", + "print(\"A-star grid based implementation using matplotlib\")\n", + "print(\"matplotlib - https://matplotlib.org/\")\n", + "\n", + "\n", + "#parameters for constructing the window\n", + "M = 100 #Rows\n", + "N = 100 #Columns\n", + "\n", + "#to calculate the presence of obstacle at a point in space\n", + "OBSTACLE_PROBABILITY = 0.25\n", + "\n", + "#for GRID Formation\n", + "GRID = np.int8(np.random.random((M, N)) > (1 - OBSTACLE_PROBABILITY))\n", + "\n", + "#start node coordinates \n", + "START_NODE = (5, 5)\n", + "\n", + "#goal node coordinates\n", + "GOAL_NODE = (M-5, N-5)\n", + "\n", + "#to construct the maze using numpy\n", + "X, Y = np.meshgrid([i for i in range(N)], [i for i in range(M)])\n", + "HEURISTIC = np.abs(X - GOAL_NODE[1]) + np.abs(Y - GOAL_NODE[0])\n", + "closed = np.zeros((M, N))\n", + "closed[START_NODE] = 1\n", + "expand = -np.ones((M, N))\n", + "action = -np.ones((M, N), dtype=np.int8)\n", + "\n", + "\n", + "x = START_NODE[0]\n", + "y = START_NODE[1]\n", + "g = 0\n", + "h = HEURISTIC[x, y]\n", + "f = g + h\n", + "DELTAS = [[1, 0],\n", + " [0, 1],\n", + " [-1, 0],\n", + " [0, -1]]\n", + "\n", + "open = [[f, g, x, y]]\n", + "\n", + "found = False\n", + "resign = False\n", + "count = 0\n", + "cost = 1\n", + "\n", + "fig, ax = plt.subplots()\n", + "route, = plt.plot([], [], 'b-')\n", + "\n", + "def init():\n", + " ax.imshow(np.logical_not(GRID), cmap=\"gray\")\n", + " ax.plot(START_NODE[1], START_NODE[0], 'ro')\n", + " ax.plot(GOAL_NODE[1], GOAL_NODE[0], 'g*')\n", + " return route,\n", + "\n", + "def get_current_route(current_node):\n", + " route = [current_node]\n", + " while route[0] != START_NODE:\n", + " node = route[0]\n", + " delta = DELTAS[action[node]]\n", + " previous_node = (node[0] - delta[0], node[1] - delta[1])\n", + " route.insert(0, previous_node)\n", + " return np.array(route)\n", + "\n", + "def animate(_):\n", + " global count, open\n", + " if len(open) == 0:\n", + " resign = True\n", + " return route,\n", + " else:\n", + " open.sort()\n", + " open.reverse()\n", + " next = open.pop()\n", + " x = next[2]\n", + " y = next[3]\n", + " g = next[1]\n", + " expand[x, y] = count\n", + " count += 1\n", + " \n", + " if (x, y) == GOAL_NODE:\n", + " found = True\n", + " open = []\n", + " else:\n", + " for i in range(len(DELTAS)):\n", + " x1 = x + DELTAS[i][0]\n", + " y1 = y + DELTAS[i][1]\n", + " if x1 >= 0 and x1 < M and y1 >=0 and y1 < N:\n", + " if closed[x1, y1] == 0 and GRID[x1, y1] == 0:\n", + " g1 = g + cost\n", + " f1 = HEURISTIC[x1, y1]\n", + " open.append([f1, g1, x1, y1])\n", + " closed[x1, y1] = 1\n", + " action[x1, y1] = i\n", + " current_route = get_current_route((x, y))\n", + " x = current_route[:, 1]\n", + " y = current_route[:, 0]\n", + " route.set_data(x, y)\n", + " return route,\n", + "\n", + "anim = animation.FuncAnimation(fig, animate, 350, interval=50, init_func=init)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Astar-matplotlib/Astar/Astar.py b/Astar-matplotlib/Astar/Astar.py new file mode 100644 index 0000000000..f39af8f12a --- /dev/null +++ b/Astar-matplotlib/Astar/Astar.py @@ -0,0 +1,122 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[10]: + + +#packages to import +from __future__ import print_function, division +import random +import numpy as np +import matplotlib.pyplot as plt +import matplotlib.animation as animation + + +print("A-star grid based implementation using matplotlib") +print("matplotlib - https://matplotlib.org/") + + +#parameters for constructing the window +M = 100 #Rows +N = 100 #Columns + +#to calculate the presence of obstacle at a point in space +OBSTACLE_PROBABILITY = 0.25 + +#for GRID Formation +GRID = np.int8(np.random.random((M, N)) > (1 - OBSTACLE_PROBABILITY)) + +#start node coordinates +START_NODE = (5, 5) + +#goal node coordinates +GOAL_NODE = (M-5, N-5) + +#to construct the maze using numpy +X, Y = np.meshgrid([i for i in range(N)], [i for i in range(M)]) +HEURISTIC = np.abs(X - GOAL_NODE[1]) + np.abs(Y - GOAL_NODE[0]) +closed = np.zeros((M, N)) +closed[START_NODE] = 1 +expand = -np.ones((M, N)) +action = -np.ones((M, N), dtype=np.int8) + + +x = START_NODE[0] +y = START_NODE[1] +g = 0 +h = HEURISTIC[x, y] +f = g + h +DELTAS = [[1, 0], + [0, 1], + [-1, 0], + [0, -1]] + +open = [[f, g, x, y]] + +found = False +resign = False +count = 0 +cost = 1 + +fig, ax = plt.subplots() +route, = plt.plot([], [], 'b-') + +def init(): + ax.imshow(np.logical_not(GRID), cmap="gray") + ax.plot(START_NODE[1], START_NODE[0], 'ro') + ax.plot(GOAL_NODE[1], GOAL_NODE[0], 'g*') + return route, + +def get_current_route(current_node): + route = [current_node] + while route[0] != START_NODE: + node = route[0] + delta = DELTAS[action[node]] + previous_node = (node[0] - delta[0], node[1] - delta[1]) + route.insert(0, previous_node) + return np.array(route) + +def animate(_): + global count, open + if len(open) == 0: + resign = True + return route, + else: + open.sort() + open.reverse() + next = open.pop() + x = next[2] + y = next[3] + g = next[1] + expand[x, y] = count + count += 1 + + if (x, y) == GOAL_NODE: + found = True + open = [] + else: + for i in range(len(DELTAS)): + x1 = x + DELTAS[i][0] + y1 = y + DELTAS[i][1] + if x1 >= 0 and x1 < M and y1 >=0 and y1 < N: + if closed[x1, y1] == 0 and GRID[x1, y1] == 0: + g1 = g + cost + f1 = HEURISTIC[x1, y1] + open.append([f1, g1, x1, y1]) + closed[x1, y1] = 1 + action[x1, y1] = i + current_route = get_current_route((x, y)) + x = current_route[:, 1] + y = current_route[:, 0] + route.set_data(x, y) + return route, + +anim = animation.FuncAnimation(fig, animate, 350, interval=50, init_func=init) +plt.show() + + +# In[ ]: + + + + diff --git a/Astar-matplotlib/LICENSE b/Astar-matplotlib/LICENSE new file mode 100644 index 0000000000..f288702d2f --- /dev/null +++ b/Astar-matplotlib/LICENSE @@ -0,0 +1,674 @@ + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. By contrast, +the GNU General Public License is intended to guarantee your freedom to +share and change all versions of a program--to make sure it remains free +software for all its users. We, the Free Software Foundation, use the +GNU General Public License for most of our software; it applies also to +any other work released this way by its authors. You can apply it to +your programs, too. + + When we speak of free software, we are referring to freedom, not +price. Our General Public Licenses are designed to make sure that you +have the freedom to distribute copies of free software (and charge for +them if you wish), that you receive source code or can get it if you +want it, that you can change the software or use pieces of it in new +free programs, and that you know you can do these things. + + To protect your rights, we need to prevent others from denying you +these rights or asking you to surrender the rights. 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But first, please read +. diff --git a/Astar-matplotlib/README.md b/Astar-matplotlib/README.md new file mode 100644 index 0000000000..ca7c0433b8 --- /dev/null +++ b/Astar-matplotlib/README.md @@ -0,0 +1,5 @@ +# Astar +This repository contains python bindings for Astar algorithm for motion planning + +# Results/ output +See Astar in [action](https://github.com/addy1997/Astar/blob/master/Video/Astar2.mov) diff --git a/Astar-matplotlib/Results/Figure_1.png b/Astar-matplotlib/Results/Figure_1.png new file mode 100644 index 0000000000..46b9086770 Binary files /dev/null and b/Astar-matplotlib/Results/Figure_1.png differ diff --git a/Astar-matplotlib/Results/Figure_2.png b/Astar-matplotlib/Results/Figure_2.png new file mode 100644 index 0000000000..7d447ac37e Binary files /dev/null and b/Astar-matplotlib/Results/Figure_2.png differ diff --git a/Astar-matplotlib/Results/Figure_3.png b/Astar-matplotlib/Results/Figure_3.png new file mode 100644 index 0000000000..5a2b2aefcb Binary files /dev/null and b/Astar-matplotlib/Results/Figure_3.png differ diff --git a/Astar-matplotlib/Results/Figure_5.png b/Astar-matplotlib/Results/Figure_5.png new file mode 100644 index 0000000000..b7aecec906 Binary files /dev/null and b/Astar-matplotlib/Results/Figure_5.png differ diff --git a/Astar-matplotlib/Video/Astar2.mov b/Astar-matplotlib/Video/Astar2.mov new file mode 100644 index 0000000000..30faf7b754 Binary files /dev/null and b/Astar-matplotlib/Video/Astar2.mov differ diff --git a/Astar-matplotlib/setup.py b/Astar-matplotlib/setup.py new file mode 100644 index 0000000000..eb19b57779 --- /dev/null +++ b/Astar-matplotlib/setup.py @@ -0,0 +1,22 @@ +import setuptools + +with open("README.md", "r") as fh: + long_description = fh.read() + +setuptools.setup( + name="A-star", + version="0.0.1", + author="Adwait Naik", + author_email="adwaitnaik2@gmail.com", + description="Python implemenation of the A-star algorithm", + long_description="A* (pronounced as "A star") is a computer algorithm that is widely used in pathfinding and graph traversal. The algorithm efficiently plots a walkable path between multiple nodes, or points, on the graph. A non-efficient way to find a path. On a map with many obstacles, pathfinding from points A to B can be difficult.", + long_description_content_type="text/markdown", + url="https://github.com/addy1997/Astar", + packages=setuptools.find_packages(), + classifiers=[ + "Programming Language :: Python :: 3", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", + ], + python_requires='>=3.6', +)