jupyter-notebooks/aula18-mapeamento-occupancy-grid.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x210a2e83430>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,8), dpi=100)\n",
    "ax = fig.add_subplot(111, aspect='equal')\n",
    "\n",
    "map_size = np.array([20, 20])\n",
    "cell_size = 1\n",
    "\n",
    "rows, cols = (map_size/cell_size).astype(int)\n",
    "\n",
    "m = np.random.uniform(low=0.0, high=1.0, size=(rows, cols))\n",
    "\n",
    "m[0,0] = 1 \n",
    "plt.imshow(m, cmap='Greys', origin='upper', extent=(0, cols, rows, 0))\n",
    "\n",
    "ax.set_xticks(np.arange(0, cols, cell_size))\n",
    "ax.set_yticks(np.arange(0, rows, cell_size))\n",
    "\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x210a3b20bb0>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from skimage.draw import line\n",
    "\n",
    "x, y = 5.5, 5.5\n",
    "xo, yo = 15.5, 10.5\n",
    "\n",
    "# x: column, y: row\n",
    "xi, yi = np.floor((1/cell_size)*np.array([x, y])).astype(int)\n",
    "xoi, yoi = np.floor((1/cell_size)*np.array([xo, yo])).astype(int)\n",
    "\n",
    "line_bresenham = np.zeros((rows, cols), dtype=np.uint8)\n",
    "rr, cc = line(yi, xi, yoi, xoi) # r0, c0, r1, c1\n",
    "line_bresenham[rr, cc] = 1\n",
    "\n",
    "fig = plt.figure(figsize=(8,8), dpi=100)\n",
    "ax = fig.add_subplot(111, aspect='equal')\n",
    "\n",
    "ax.imshow(m, cmap='Greys', extent=(0, cols, rows, 0))\n",
    "ax.imshow(line_bresenham, cmap='Reds', extent=(0, cols, rows, 0), alpha=.5)\n",
    "\n",
    "ax.set_xticks(np.arange(0, cols, cell_size))\n",
    "ax.set_yticks(np.arange(0, rows, cell_size))\n",
    "\n",
    "ax.plot([x, xo], [y, yo], 'r-', linewidth=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Para praticar\n",
    "\n",
    "- Marcar todas as células que a linha intercepta\n",
    "    - https://gamedev.stackexchange.com/questions/81267/how-do-i-generalise-bresenhams-line-algorithm-to-floating-point-endpoints\n",
    "- Considerar sensores com múltiplas leituras\n",
    "- Realizar a exploração e gerar o mapa de um ambiente"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}