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update docs
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AerialNavigation/rocket_powered_landing/rocket_powered_landing.ipynb

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ArmNavigation/two_joint_arm_to_point_control/Planar_Two_Link_IK.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.6"
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"version": "3.6.7"
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}
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},
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"nbformat": 4,

PathTracking/cgmres_nmpc/cgmres_nmpc.ipynb

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"\n",
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"Partial differential equations of the Hamiltonian are:\n",
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"\n",
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"$\\frac{\\partial H}{\\partial \\bf{x}}=\\\\ \n",
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"[\\frac{\\partial H}{\\partial x}= 0,\\\\\n",
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"\\frac{\\partial H}{\\partial y}= 0,\\\\\n",
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"\\frac{\\partial H}{\\partial \\theta}= -\\lambda_1vsin\\theta+\\lambda_2vcos\\theta,\\\\\n",
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"\\frac{\\partial H}{\\partial v}=-\\lambda_1cos\\theta+\\lambda_2sin\\theta+\\lambda_3\\frac{1}{WB}sin(u_{\\delta})]\\\\\n",
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"$\n",
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"\n",
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"\n",
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"$\\frac{\\partial H}{\\partial \\bf{u}}=\\\\ \n",
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"[\\frac{\\partial H}{\\partial u_a}= u_a+\\lambda_4+2\\rho_1u_a,\\\\\n",
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"\\frac{\\partial H}{\\partial u_\\delta}= u_\\delta+\\lambda_3\\frac{v}{WB}cos(u_{\\delta})+2\\rho_2u_\\delta\\\\\n",
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"\\frac{\\partial H}{\\partial d_a}= -\\phi_a+2\\rho_1d_a,\\\\\n",
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"\\frac{\\partial H}{\\partial d_\\delta}=-\\phi_\\delta+2\\rho_2d_\\delta]\\\\\n",
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"$"
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"$\\begin{equation*}\n",
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"\\frac{\\partial H}{\\partial \\bf{x}}=\\\\ \n",
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"\\begin{bmatrix}\n",
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"\\frac{\\partial H}{\\partial x}= 0&\\\\\n",
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"\\frac{\\partial H}{\\partial y}= 0&\\\\\n",
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"\\frac{\\partial H}{\\partial \\theta}= -\\lambda_1vsin\\theta+\\lambda_2vcos\\theta&\\\\\n",
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"\\frac{\\partial H}{\\partial v}=-\\lambda_1cos\\theta+\\lambda_2sin\\theta+\\lambda_3\\frac{1}{WB}sin(u_{\\delta})&\\\\\n",
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"\\end{bmatrix}\n",
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"\\\\\n",
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"\\end{equation*}$\n",
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"\n",
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"\n",
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"$\\begin{equation*}\n",
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"\\frac{\\partial H}{\\partial \\bf{u}}=\\\\ \n",
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"\\begin{bmatrix}\n",
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"\\frac{\\partial H}{\\partial u_a}= u_a+\\lambda_4+2\\rho_1u_a&\\\\\n",
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"\\frac{\\partial H}{\\partial u_\\delta}= u_\\delta+\\lambda_3\\frac{v}{WB}cos(u_{\\delta})+2\\rho_2u_\\delta&\\\\\n",
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"\\frac{\\partial H}{\\partial d_a}= -\\phi_a+2\\rho_1d_a&\\\\\n",
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"\\frac{\\partial H}{\\partial d_\\delta}=-\\phi_\\delta+2\\rho_2d_\\delta&\\\\\n",
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"\\end{bmatrix}\n",
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"\\\\\n",
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"\\end{equation*}$"
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]
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},
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{
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.6"
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"version": "3.6.7"
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}
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},
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"nbformat": 4,

PathTracking/model_predictive_speed_and_steer_control/Model_predictive_speed_and_steering_control.ipynb

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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.6"
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"version": "3.6.7"
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}
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},
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"nbformat": 4,

SLAM/FastSLAM1/FastSLAM1.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Simulation\n",
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"\n",
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"This is a feature based SLAM example using FastSLAM 1.0.\n",
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"\n",
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"The blue line is ground truth, the black line is dead reckoning, the red\n",
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"line is the estimated trajectory with FastSLAM.\n",
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"\n",
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"The red points are particles of FastSLAM.\n",
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"\n",
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"Black points are landmarks, blue crosses are estimated landmark\n",
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"positions by FastSLAM.\n",
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"\n",
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"\n",
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"![gif](https://github.com/AtsushiSakai/PythonRobotics/raw/master/SLAM/FastSLAM1/animation.gif)"
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]
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},
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"\n",
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"The figure shows 100 particles distributed uniformly between [-0.5, 0.5] with the weights of each particle distributed according to a Gaussian funciton. \n",
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"\n",
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"The resampling picks $i \\in 1,...,N$ particles with probability to pick particle with index $i \\propto \\omega_i $, where $\\omega_i$ is the weight of that particle\n",
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"The resampling picks \n",
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"\n",
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"$i \\in 1,...,N$ particles with probability to pick particle with index $i ∝ \\omega_i$, where $\\omega_i$ is the weight of that particle\n",
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"\n",
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"\n",
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"To get the intuition of the resampling step we will look at a set of particles which are initialized with a given x location and weight. After the resampling the particles are more concetrated in the location where they had the highest weights. This is also indicated by the indices \n"
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.5"
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"version": "3.6.7"
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}
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},
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"nbformat": 4,

docs/jupyternotebook2rst.py

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# print(notebook_path_list)
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for npath in notebook_path_list:
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generate_rst(npath)
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if "template" not in npath:
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generate_rst(npath)
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print("done!!")
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