develop.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "pybullet build time: Sep 29 2023 11:48:38\n"
     ]
    }
   ],
   "source": [
    "import pybullet as pb\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xml.etree.ElementTree as etxml\n",
    "import pkg_resources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "urdf = etxml.parse(pkg_resources.resource_filename('gym_pybullet_drones', 'assets/cf2p.urdf')).getroot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(urdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'arm': '0.0397',\n",
       " 'kf': '3.16e-10',\n",
       " 'km': '7.94e-12',\n",
       " 'thrust2weight': '2.25',\n",
       " 'max_speed_kmh': '30',\n",
       " 'gnd_eff_coeff': '11.36859',\n",
       " 'prop_radius': '2.31348e-2',\n",
       " 'drag_coeff_xy': '9.1785e-7',\n",
       " 'drag_coeff_z': '10.311e-7',\n",
       " 'dw_coeff_1': '2267.18',\n",
       " 'dw_coeff_2': '.16',\n",
       " 'dw_coeff_3': '-.11'}"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urdf[0].attrib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['__class__', '__copy__', '__deepcopy__', '__delattr__', '__delitem__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getitem__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__len__', '__lt__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__setitem__', '__setstate__', '__sizeof__', '__str__', '__subclasshook__', 'append', 'attrib', 'clear', 'extend', 'find', 'findall', 'findtext', 'get', 'insert', 'items', 'iter', 'iterfind', 'itertext', 'keys', 'makeelement', 'remove', 'set', 'tag', 'tail', 'text']\n"
     ]
    }
   ],
   "source": [
    "print(dir(urdf[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Element 'joint' at 0x7fc69a4c74c0>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urdf[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['__class__', '__copy__', '__deepcopy__', '__delattr__', '__delitem__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getitem__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__len__', '__lt__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__setitem__', '__setstate__', '__sizeof__', '__str__', '__subclasshook__', 'append', 'attrib', 'clear', 'extend', 'find', 'findall', 'findtext', 'get', 'insert', 'items', 'iter', 'iterfind', 'itertext', 'keys', 'makeelement', 'remove', 'set', 'tag', 'tail', 'text']\n"
     ]
    }
   ],
   "source": [
    "print(dir(urdf[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('name', 'base_link')]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urdf[1].items()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Element 'robot' at 0x7fc69a4c6c00>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'inertial'"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urdf[1][0].tag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'rpy': '0 0 0', 'xyz': '0 0 0'}"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urdf[1][0][0].attrib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[0., 0., 0., 0., 0., 0.]]), array([[0.]]))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.zeros((1, 6))\n",
    "b = np.zeros((1, 1))\n",
    "a,b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 0., 0., 0., 0., 0., 0.]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.concatenate((a, b), axis=1)"
   ]
  }
 ],
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   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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