bullet3/examples/pybullet/notebooks/HelloPyBullet.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pybullet as p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p.connect(p.DIRECT)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p.loadURDF(\"plane.urdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "r2d2=p.loadURDF(\"r2d2.urdf\",[0,0,0.5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p.getNumBodies()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "joint 0 name= base_to_right_leg\n",
      "joint 1 name= right_base_joint\n",
      "joint 2 name= right_front_wheel_joint\n",
      "joint 3 name= right_back_wheel_joint\n",
      "joint 4 name= base_to_left_leg\n",
      "joint 5 name= left_base_joint\n",
      "joint 6 name= left_front_wheel_joint\n",
      "joint 7 name= left_back_wheel_joint\n",
      "joint 8 name= gripper_extension\n",
      "joint 9 name= left_gripper_joint\n",
      "joint 10 name= left_tip_joint\n",
      "joint 11 name= right_gripper_joint\n",
      "joint 12 name= right_tip_joint\n",
      "joint 13 name= head_swivel\n",
      "joint 14 name= tobox\n"
     ]
    }
   ],
   "source": [
    "for i in range (p.getNumJoints(r2d2)):\n",
    "    jointInfo=p.getJointInfo(r2d2,i)\n",
    "    print(\"joint\",jointInfo[0],\"name=\",jointInfo[1].decode('ascii'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pos = 0.00000,0.00000,0.50000   \n",
      "pos = 0.00000,-0.00000,0.49983   \n",
      "pos = 0.00000,-0.00000,0.49948   \n",
      "pos = 0.00000,-0.00000,0.49896   \n",
      "pos = 0.00000,-0.00000,0.49826   \n",
      "pos = 0.00000,-0.00000,0.49740   \n",
      "pos = 0.00000,-0.00000,0.49636   \n",
      "pos = 0.00000,-0.00000,0.49514   \n",
      "pos = 0.00000,-0.00000,0.49375   \n",
      "pos = 0.00000,-0.00000,0.49219   \n"
     ]
    }
   ],
   "source": [
    "p.setGravity(0,0,-10)\n",
    "precision=5\n",
    "for i in range (10):\n",
    "    pos,orn = p.getBasePositionAndOrientation(r2d2)\n",
    "    posmsg='pos = {posx:.{prec}f},{posy:.{prec}f},{posz:.{prec}f}   '.format(posx=pos[0],posy=pos[1],posz=pos[2], prec=precision)\n",
    "    print(posmsg)\n",
    "    p.stepSimulation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "p.stepSimulation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "camTargetPos = [0,0,0]\n",
    "cameraUp = [0,0,1]\n",
    "cameraPos = [1,1,1]\n",
    "\n",
    "pitch = -10.0\n",
    "yaw = 60\n",
    "roll=0\n",
    "upAxisIndex = 2\n",
    "camDistance = 4\n",
    "pixelWidth = 320\n",
    "pixelHeight = 200\n",
    "nearPlane = 0.01\n",
    "farPlane = 100\n",
    "fov = 60\n",
    "viewMatrix = p.computeViewMatrixFromYawPitchRoll(camTargetPos, camDistance, yaw, pitch, roll, upAxisIndex)\n",
    "aspect = pixelWidth / pixelHeight;\n",
    "projectionMatrix = p.computeProjectionMatrixFOV(fov, aspect, nearPlane, farPlane);\n",
    "img_arr = p.getCameraImage(pixelWidth, pixelHeight, viewMatrix,projectionMatrix, shadow=1,lightDirection=[1,1,1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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UIR4JvWgUdRD2NBTSmVyGLfwSelFb6izqaci7F1B+mEdCL2pBE0W9FxJ8EVKG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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108feb4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w=img_arr[0] #width of the image, in pixels\n",
    "h=img_arr[1] #height of the image, in pixels\n",
    "rgb=img_arr[2] #color data RGB\n",
    "plt.imshow(rgb,interpolation='none')\n",
    "plt.draw()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}