ITR_Assignment4_Vignesh_Ramakrishnan_21310037.ipynb

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    "colab": {
      "name": "ITR_Assignment4_Vignesh_Ramakrishnan_21310037.ipynb",
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      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "uPVblZgHmkn2"
      },
      "source": [
        "#Vignesh Ramakrishnan\n",
        "#21310037\n",
        "#Importing libraries\n",
        "%matplotlib inline\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import scipy.integrate as integrate \n",
        "import matplotlib.animation as animation\n",
        "from matplotlib.animation import FuncAnimation\n",
        "from matplotlib import rc\n",
        "from IPython.display import HTML\n",
        "from numpy import sin, cos,arctan,arccos\n",
        "from collections import deque"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "404-z4Gw9EZn"
      },
      "source": [
        "### Task1: Stanford Manipulator (RRP) Inverse Kinematics\n",
        "Inputs: fixed lengths $l_1$, $l_2$(fixed length of links with revolute joints),Current end-effector position $P_0$($P_x$,$P_y$,$P_z$)\n",
        "\n",
        "Outputs:\n",
        "$d_3$ (variable length of prismatic joint), $\\theta_1$,$\\theta_2$(variable revolute joint angles)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SuHVEibqk_IT"
      },
      "source": [
        "\n",
        "\n",
        "\n",
        "#Taking fixed values\n",
        "l_1=5\n",
        "l_2=1\n",
        "\n",
        "Px=-1\n",
        "Py= 3**0.5\n",
        "Pz=5\n",
        "P0=np.array([Px,Py,Pz])\n"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HgjoqWIeMW-z",
        "outputId": "9e1bfec3-8387-4500-f5c9-c8d1b842b597"
      },
      "source": [
        "#Inverse Position Kinematics for Stanford manipulator\n",
        "def Inv_Pos_Kin_Stanford(P0,l_1,l_2):\n",
        "  P_x=P0[0]\n",
        "  P_y=P0[1]\n",
        "  P_z=P0[2]\n",
        "  r= ((P_x**2) + (P_y**2))**0.5 #revolute link radius\n",
        "  phi= np.arctan2(P_y,P_x) # revolute link angle\n",
        " \n",
        "  theta_1=np.arctan2(P_x,P_y)- np.arctan2(l_2,((r**2)-(l_2**2))**0.5 ) # theta_1=np.arctan2(P_x,P_y)- np.arctan2(l_2,-((r**2)-(l_2**2))**0.5 ) # also valid\n",
        "\n",
        "  #if theta_1 < 0 :\n",
        "  #  theta_1=np.arctan2(P_x,P_y)- np.arctan2(l_2,-((r**2)-(l_2**2))**0.5 )\n",
        "    \n",
        "\n",
        "  l_hor=((P_x*np.cos(theta_1))+(P_y*np.sin(theta_1))) #Horizontal position of joint 2\n",
        "  l_vert=l_1-P_z #Vertical position of joint 2\n",
        "\n",
        "\n",
        "\n",
        "  theta_2=np.arctan2(l_hor,l_vert) #  theta_2=np.arctan2(-l_hor,-l_vert) #also valid\n",
        "\n",
        "  #if theta_2 < 0 :\n",
        "  #  theta_2=np.arctan2(-l_hor,-l_vert)\n",
        "  \n",
        "  d_3= (l_hor* np.sin(theta_2))+(l_vert* np.cos(theta_2))\n",
        "  return np.array([np.degrees(theta_1),np.degrees(theta_2),d_3])\n",
        "\n",
        "\n",
        "#Run function\n",
        "Inv_Pos_Kin_Stanford(P0,l_1,l_2)\n"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-60., -90.,   2.])"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ig4WVBzRmRKt"
      },
      "source": [
        "### Task 2: SCARA Manipulator (RRP) Inverse Kinematics\n",
        "Inputs: fixed lengths $l_1$, $l_2$(fixed length of links with revolute joints),Current end-effector position $P_0$($P_x$,$P_y$,$P_z$)\n",
        "\n",
        "Outputs:\n",
        "$d_3$ (variable length of prismatic joint), $\\theta_1$,$\\theta_2$(variable revolute joint angles)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h4J-QJG6vWAJ"
      },
      "source": [
        "#Taking fixed values\n",
        "l_1=1.5\n",
        "l_2=1\n",
        "h= 6\n",
        "Px=-1\n",
        "Py= 3**0.5\n",
        "Pz=5\n",
        "P0=np.array([Px,Py,Pz])\n"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u2lQ2YxNZ6Ej",
        "outputId": "92b8f59c-9f0e-4f25-c139-81b7966ee642"
      },
      "source": [
        "#Inverse Position Kinematics for SCARA manipulator\n",
        "def Inv_Pos_Kin_SCARA(P0,l_1,l_2,h):\n",
        "  P_x=P0[0]\n",
        "  P_y=P0[1]\n",
        "  P_z=P0[2]\n",
        "  theta_2=np.arccos(((P_x**2+P_y**2)-(l_1**2+l_2**2))/(2*l_1*l_2)) # + or -\n",
        "  theta_1=np.arctan2(((l_2*P_x*np.sin(theta_2))+P_y*(l_1+l_2*np.cos(theta_2))),(-(l_2*P_y*np.sin(theta_2))+P_x*(l_1+l_2*np.cos(theta_2))))\n",
        "  d_3=h-P_z\n",
        "  return np.array([np.degrees(theta_1),np.degrees(theta_2),d_3])\n",
        "\n",
        "\n",
        "#Run function\n",
        "Inv_Pos_Kin_SCARA(P0,l_1,l_2,h)\n"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([148.95502437,  75.52248781,   1.        ])"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w-yRgrQWhxLe"
      },
      "source": [
        "### Task 3 : Calculating joint velocities using end-effector cartesian velocities"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2s--HESbLLt0"
      },
      "source": [
        "\n",
        "#Rotational matrix along x\n",
        "def RotX(theta):\n",
        "  theta=np.radians(theta)\n",
        "  return np.array([[1,0,0,0],[0,np.cos(theta),-np.sin(theta),0],[0,np.sin(theta),np.cos(theta),0],[0,0,0,1]])\n",
        "\n",
        "\n",
        "#Rotational matrix along y\n",
        "def RotY(theta):\n",
        "  theta=np.radians(theta)\n",
        "  return np.array([[np.cos(theta),0,-np.sin(theta),0],[0,1,0,0],[np.sin(theta),0,np.cos(theta),0],[0,0,0,1]])\n",
        "\n",
        "\n",
        "#Rotational matrix along z\n",
        "def RotZ(theta):\n",
        "  theta=np.radians(theta)\n",
        "  return np.array([[np.cos(theta),-np.sin(theta),0,0],[np.sin(theta),np.cos(theta),0,0],[0,0,1,0],[0,0,0,1]])\n",
        "\n",
        "\n",
        "#Translational matrix along x\n",
        "def TransX(dist):\n",
        "  return np.array([[1,0,0,dist],[0,1,0,0],[0,0,1,0],[0,0,0,1]])\n",
        "\n",
        "#Translational matrix along y\n",
        "def TransY(dist):\n",
        "  return np.array([[1,0,0,0],[0,1,0,dist],[0,0,1,0],[0,0,0,1]])\n",
        "\n",
        "#Translational matrix along z\n",
        "def TransZ(dist):\n",
        "  return np.array([[1,0,0,0],[0,1,0,0],[0,0,1,dist],[0,0,0,1]])"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "axvHDRd6KAJT",
        "outputId": "7f81445f-6743-4275-b6ef-f3fa8a477349"
      },
      "source": [
        " #Input DH matrix code not working so hardcoding matrix\n",
        " #Jacobian calculator\n",
        "dh_matrix=np.array([[10,30,0,-90],[5,25,0,90],[2,0,0,0]])\n",
        "Lnature=[0,0,1]\n",
        "link_no=3\n",
        "def Jacobian(link_no,Lnature):\n",
        "  \n",
        "  T=np.array([[0,0,0,0]])\n",
        "  zi_arr=np.array([[0,0,0]])\n",
        "  zi=np.transpose(np.array([0,0,0]))\n",
        "  d0i=np.transpose(np.array([0,0,0,0]))\n",
        "  d0i_arr=np.array([[0,0,0]])\n",
        "  Tcurr=np.array([[1,0,0,0],[0,1,0,0],[0,0,1,0],[0,0,0,1]])\n",
        "  Rcurr=np.array([[1,0,0],[0,1,0],[0,0,1]])\n",
        "  for i in dh_matrix:\n",
        "    d=i[0]\n",
        "    theta=i[1]\n",
        "    a=i[2]\n",
        "    alpha=i[3]\n",
        "    Ti= RotZ(theta) @ TransZ(d) @ RotX(alpha) @ TransX(a)\n",
        "    Rz=np.array(RotZ(theta))\n",
        "    Rx=np.array(RotX(alpha))\n",
        "    Ri= Rz[0:3,0:3] @ Rx[0:3,0:3]\n",
        "    Rcurr= Rcurr @ Ri\n",
        "    Tcurr=Tcurr @ Ti\n",
        "    d0i=(Tcurr[0:3,-1])\n",
        "    zi= (Rcurr[:,-1])\n",
        "    d0i_arr=np.vstack((d0i_arr,d0i))\n",
        "    zi_arr=np.vstack((zi_arr,zi))\n",
        "    #print(zi_arr)\n",
        "    T=np.concatenate((T,Ti))\n",
        "  T=np.delete(T,0,axis=0)\n",
        "  d0n=d0i #Accessing after all iterations, gives end effector position d0n\n",
        "  #print(d0n)\n",
        "  doi_arr_2=np.array([d0n,d0n,d0n])-np.delete(d0i_arr,0,axis=0)\n",
        "  \n",
        "  zi_arr=np.delete(zi_arr,0,axis=0)\n",
        "  Jac=np.zeros(6)\n",
        "  for j in range(0,link_no-1):\n",
        "    Jac=np.append(Jac,np.array([np.cross(zi_arr[j],doi_arr_2[j]),(zi_arr[j])]))\n",
        "  #Jac=np.delete(Jac,0,axis=0)\n",
        "  #print(Jac)\n",
        "  #for j in range(0,link_no-1):\n",
        "   # ddiff=d0n-d0i_arr[j]\n",
        "    #print(ddiff)\n",
        "    #Jac[1,0:3]=np.cross(np.transpose(zi_arr[j]),np.atleast_2d(np.transpose(ddiff)))\n",
        "    #if (Lnature[j]==0):\n",
        "     # Jac[1,:]= np.stack(np.cross(np.transpose(zi_arr[j]),np.atleast_2d(np.transpose(ddiff))),(np.transpose(ddiff))) #print('val',np.atleast_2d(np.transpose(ddiff)))\n",
        "    #else :\n",
        "     # Jac[1,:]=np.stack(np.transpose(zi_arr[j]),np.zeros_like(np.transpose(zi_arr[j])))\n",
        "  #print(Jac)\n",
        "  return Jac\n",
        "\n",
        "Jacobian(link_no,Lnature)"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
              "        0.00000000e+00,  0.00000000e+00,  1.56977113e+00,  9.06307787e-01,\n",
              "       -8.45236523e-01, -5.00000000e-01,  8.66025404e-01,  6.12323400e-17,\n",
              "        1.66533454e-16, -1.11022302e-16, -5.55111512e-17,  3.65998151e-01,\n",
              "        2.11309131e-01,  9.06307787e-01])"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I53YB65uvR6h",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 197
        },
        "outputId": "12da738b-9292-4a5c-9c94-59f2c9817b88"
      },
      "source": [
        "v_x=10\n",
        "v_y=15\n",
        "v_z=20\n",
        "cartdot=np.array([v_x,v_y,v_z])\n",
        "J_1=(Jacobian(link_no,Lnature))\n",
        "Jinv=np.linalg.pinv(J_1.reshape(6,link_no))\n",
        "qdot=Jinv.dot(cartdot)\n"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-36-5efccd43cfda>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mJ_1\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mJacobian\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlink_no\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mLnature\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mJinv\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpinv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mJ_1\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mlink_no\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mqdot\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mJinv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcartdot\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m: shapes (3,6) and (3,) not aligned: 6 (dim 1) != 3 (dim 0)"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4FHr-1KH5ShJ"
      },
      "source": [
        "### Task 4: Read about Euler Angles from textbook: done"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XObA1W1c5dnJ"
      },
      "source": [
        "### Task 5:Spherical wrist, toolframe and inverse kinematics: Reading complete"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OaEJHuh25qzh"
      },
      "source": [
        "### Task 6: Inverse Kinematics of Spherical wrist\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RYh_Tv9O-tHX"
      },
      "source": [
        "#Taking fixed values\n",
        "d_1=1\n",
        "Px=-1\n",
        "Py= 3**0.5\n",
        "Pz=5\n",
        "P0=np.array([Px,Py,Pz])\n"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6BGcrpUg-v0n",
        "outputId": "dafc7c77-5fdb-4a80-997d-ea4b0ca9c255"
      },
      "source": [
        "#Inverse Position Kinematics for Spherical wrist manipulator\n",
        "def Inv_Pos_Kin_Sphericalwrist(P0,d_1):\n",
        "  P_x=P0[0]\n",
        "  P_y=P0[1]\n",
        "  P_z=P0[2]\n",
        "  r= (P_x**2 + P_y**2)**0.5\n",
        "  theta_1= np.arctan2(P_x,P_y)\n",
        "  s=P_z-d_1\n",
        "  d_3= (r**2 + s**2)**0.5\n",
        "  theta_2=np.arctan2(r,s)+ 0.5*np.pi\n",
        "  return np.array([np.degrees(theta_1),np.degrees(theta_2),d_3])\n",
        "\n",
        "\n",
        "#Run function\n",
        "Inv_Pos_Kin_Sphericalwrist(P0,d_1)\n"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-30.        , 116.56505118,   4.47213595])"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xmkJJHEuA3vW"
      },
      "source": [
        "### Task 7: DH parameters for 3D printer (PPP)\n",
        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)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iPsffGKjDvhl",
        "outputId": "dda8764a-d911-41c8-dc02-269257916066"
      },
      "source": [
        "d_1=2\n",
        "d_2=5\n",
        "d_3=1\n",
        "\n",
        "\n",
        "dh_matrix=np.array([[2,0,0,-90],[5,90,0,-90],[1,0,0,0]])\n",
        "Lnature=[1,1,1]\n",
        "link_no=3\n",
        "Jacobian(link_no,Lnature)"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00,  0.0000000e+00,\n",
              "        0.0000000e+00,  0.0000000e+00,  1.3792751e-16, -6.1232340e-17,\n",
              "        1.0000000e+00,  0.0000000e+00,  1.0000000e+00,  6.1232340e-17,\n",
              "        0.0000000e+00,  6.1232340e-17,  6.1232340e-17, -1.0000000e+00,\n",
              "        6.1232340e-17, -6.1232340e-17])"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AeWjpP3zDmpN"
      },
      "source": [
        "### Task 8:Inverse Kinematics for 3D printer\n",
        "Consider nozzle position $P_0(P_x,P_y,P_z)$.Then, for the inverse kinematics, we get \n",
        "$d_1=P_z$, $d_2=-P_y$, $d_3=P_x$ as per the image from Task 6"
      ]
    }
  ]
}