|
6 | 6 | "metadata": {}, |
7 | 7 | "outputs": [ |
8 | 8 | { |
9 | | - "ename": "ModuleNotFoundError", |
10 | | - "evalue": "No module named 'mdh.models'", |
11 | | - "output_type": "error", |
12 | | - "traceback": [ |
13 | | - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", |
14 | | - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", |
15 | | - "\u001b[0;32m<ipython-input-1-016134810506>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mmdh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlink\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmdh_params\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mJointType\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mmdh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkinematic_chain\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mKinematicChain\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mmdh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodels\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpuma500\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", |
16 | | - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'mdh.models'" |
| 9 | + "name": "stdout", |
| 10 | + "output_type": "stream", |
| 11 | + "text": [ |
| 12 | + "0.1.2\n" |
17 | 13 | ] |
18 | 14 | } |
19 | 15 | ], |
|
24 | 20 | "import mdh\n", |
25 | 21 | "from mdh.link import mdh_params, JointType\n", |
26 | 22 | "from mdh.kinematic_chain import KinematicChain\n", |
27 | | - "from mdh.models import puma500\n", |
| 23 | + "from mdh.robots import puma560\n", |
28 | 24 | "\n", |
29 | 25 | "import pandas\n", |
30 | 26 | "\n", |
|
37 | 33 | "metadata": {}, |
38 | 34 | "outputs": [ |
39 | 35 | { |
40 | | - "ename": "AttributeError", |
41 | | - "evalue": "module 'mdh' has no attribute 'models'", |
42 | | - "output_type": "error", |
43 | | - "traceback": [ |
44 | | - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", |
45 | | - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", |
46 | | - "\u001b[0;32m<ipython-input-2-ff10bdcf3762>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mparams\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmdh\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodels\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpuma500\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[0m\u001b[1;32m 2\u001b[0m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpandas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", |
47 | | - "\u001b[0;31mAttributeError\u001b[0m: module 'mdh' has no attribute 'models'" |
| 36 | + "data": { |
| 37 | + "text/html": [ |
| 38 | + "<div>\n", |
| 39 | + "<style scoped>\n", |
| 40 | + " .dataframe tbody tr th:only-of-type {\n", |
| 41 | + " vertical-align: middle;\n", |
| 42 | + " }\n", |
| 43 | + "\n", |
| 44 | + " .dataframe tbody tr th {\n", |
| 45 | + " vertical-align: top;\n", |
| 46 | + " }\n", |
| 47 | + "\n", |
| 48 | + " .dataframe thead th {\n", |
| 49 | + " text-align: right;\n", |
| 50 | + " }\n", |
| 51 | + "</style>\n", |
| 52 | + "<table border=\"1\" class=\"dataframe\">\n", |
| 53 | + " <thead>\n", |
| 54 | + " <tr style=\"text-align: right;\">\n", |
| 55 | + " <th></th>\n", |
| 56 | + " <th>alpha</th>\n", |
| 57 | + " <th>a</th>\n", |
| 58 | + " <th>theta</th>\n", |
| 59 | + " <th>d</th>\n", |
| 60 | + " <th>type</th>\n", |
| 61 | + " </tr>\n", |
| 62 | + " </thead>\n", |
| 63 | + " <tbody>\n", |
| 64 | + " <tr>\n", |
| 65 | + " <th>0</th>\n", |
| 66 | + " <td>0.000000</td>\n", |
| 67 | + " <td>0.0000</td>\n", |
| 68 | + " <td>0.0</td>\n", |
| 69 | + " <td>0.0000</td>\n", |
| 70 | + " <td>1</td>\n", |
| 71 | + " </tr>\n", |
| 72 | + " <tr>\n", |
| 73 | + " <th>1</th>\n", |
| 74 | + " <td>-1.570796</td>\n", |
| 75 | + " <td>0.0000</td>\n", |
| 76 | + " <td>0.0</td>\n", |
| 77 | + " <td>0.0000</td>\n", |
| 78 | + " <td>1</td>\n", |
| 79 | + " </tr>\n", |
| 80 | + " <tr>\n", |
| 81 | + " <th>2</th>\n", |
| 82 | + " <td>0.000000</td>\n", |
| 83 | + " <td>0.6127</td>\n", |
| 84 | + " <td>0.0</td>\n", |
| 85 | + " <td>0.0000</td>\n", |
| 86 | + " <td>1</td>\n", |
| 87 | + " </tr>\n", |
| 88 | + " <tr>\n", |
| 89 | + " <th>3</th>\n", |
| 90 | + " <td>0.000000</td>\n", |
| 91 | + " <td>0.5716</td>\n", |
| 92 | + " <td>0.0</td>\n", |
| 93 | + " <td>0.1639</td>\n", |
| 94 | + " <td>1</td>\n", |
| 95 | + " </tr>\n", |
| 96 | + " <tr>\n", |
| 97 | + " <th>4</th>\n", |
| 98 | + " <td>-1.570796</td>\n", |
| 99 | + " <td>0.0000</td>\n", |
| 100 | + " <td>0.0</td>\n", |
| 101 | + " <td>0.1157</td>\n", |
| 102 | + " <td>1</td>\n", |
| 103 | + " </tr>\n", |
| 104 | + " </tbody>\n", |
| 105 | + "</table>\n", |
| 106 | + "</div>" |
| 107 | + ], |
| 108 | + "text/plain": [ |
| 109 | + " alpha a theta d type\n", |
| 110 | + "0 0.000000 0.0000 0.0 0.0000 1\n", |
| 111 | + "1 -1.570796 0.0000 0.0 0.0000 1\n", |
| 112 | + "2 0.000000 0.6127 0.0 0.0000 1\n", |
| 113 | + "3 0.000000 0.5716 0.0 0.1639 1\n", |
| 114 | + "4 -1.570796 0.0000 0.0 0.1157 1" |
| 115 | + ] |
| 116 | + }, |
| 117 | + "execution_count": 2, |
| 118 | + "metadata": {}, |
| 119 | + "output_type": "execute_result" |
| 120 | + } |
| 121 | + ], |
| 122 | + "source": [ |
| 123 | + "params = puma560()\n", |
| 124 | + "df = pandas.DataFrame(params)\n", |
| 125 | + "df.head()" |
| 126 | + ] |
| 127 | + }, |
| 128 | + { |
| 129 | + "cell_type": "code", |
| 130 | + "execution_count": 3, |
| 131 | + "metadata": {}, |
| 132 | + "outputs": [ |
| 133 | + { |
| 134 | + "name": "stdout", |
| 135 | + "output_type": "stream", |
| 136 | + "text": [ |
| 137 | + "1: alpha: 0.0deg a: 0.0m theta: 0e+00deg d: 0.0\n", |
| 138 | + "1: alpha: -0.0deg a: 0.0m theta: 0e+00deg d: 0.0\n", |
| 139 | + "1: alpha: 0.0deg a: 0.6m theta: 0e+00deg d: 0.0\n", |
| 140 | + "1: alpha: 0.0deg a: 0.6m theta: 0e+00deg d: 0.2\n", |
| 141 | + "1: alpha: -0.0deg a: 0.0m theta: 0e+00deg d: 0.1\n", |
| 142 | + "1: alpha: 0.0deg a: 0.0m theta: 0.05deg d: 0.1\n" |
48 | 143 | ] |
49 | 144 | } |
50 | 145 | ], |
51 | 146 | "source": [ |
52 | | - "params = mdh.models.puma500()\n", |
53 | | - "df = pandas.DataFrame(params)" |
| 147 | + "puma = KinematicChain.from_parameters(params)\n", |
| 148 | + "for l in puma:\n", |
| 149 | + " print(l)" |
54 | 150 | ] |
55 | 151 | }, |
56 | 152 | { |
57 | 153 | "cell_type": "code", |
58 | 154 | "execution_count": 4, |
59 | 155 | "metadata": {}, |
| 156 | + "outputs": [ |
| 157 | + { |
| 158 | + "name": "stdout", |
| 159 | + "output_type": "stream", |
| 160 | + "text": [ |
| 161 | + "Can't reach: [0.015, 0.015, 0.15]m\n" |
| 162 | + ] |
| 163 | + } |
| 164 | + ], |
| 165 | + "source": [ |
| 166 | + "try:\n", |
| 167 | + " rads = puma.inverse([.015,.015,.15])\n", |
| 168 | + " # degs = np.rad2deg(rads)\n", |
| 169 | + " print(rads)\n", |
| 170 | + "except mdh.UnReachable as e:\n", |
| 171 | + " print(e)" |
| 172 | + ] |
| 173 | + }, |
| 174 | + { |
| 175 | + "cell_type": "code", |
| 176 | + "execution_count": 5, |
| 177 | + "metadata": {}, |
| 178 | + "outputs": [], |
| 179 | + "source": [ |
| 180 | + "from scipy.spatial.transform import Rotation as R" |
| 181 | + ] |
| 182 | + }, |
| 183 | + { |
| 184 | + "cell_type": "code", |
| 185 | + "execution_count": 8, |
| 186 | + "metadata": {}, |
| 187 | + "outputs": [], |
| 188 | + "source": [ |
| 189 | + "from math import pi, atan2" |
| 190 | + ] |
| 191 | + }, |
| 192 | + { |
| 193 | + "cell_type": "code", |
| 194 | + "execution_count": 11, |
| 195 | + "metadata": {}, |
| 196 | + "outputs": [ |
| 197 | + { |
| 198 | + "name": "stdout", |
| 199 | + "output_type": "stream", |
| 200 | + "text": [ |
| 201 | + "<scipy.spatial.transform.rotation.Rotation object at 0x7f6ed5e802d0>\n" |
| 202 | + ] |
| 203 | + } |
| 204 | + ], |
| 205 | + "source": [ |
| 206 | + "r=R.from_euler('zyx', [-90,atan2(10,10)*180/pi,90], degrees=True)\n", |
| 207 | + "print(r)" |
| 208 | + ] |
| 209 | + }, |
| 210 | + { |
| 211 | + "cell_type": "code", |
| 212 | + "execution_count": 17, |
| 213 | + "metadata": {}, |
60 | 214 | "outputs": [ |
61 | 215 | { |
62 | 216 | "data": { |
63 | 217 | "text/plain": [ |
64 | | - "'0.1.2'" |
| 218 | + "array([-90., 45., 90.])" |
65 | 219 | ] |
66 | 220 | }, |
67 | | - "execution_count": 4, |
| 221 | + "execution_count": 17, |
68 | 222 | "metadata": {}, |
69 | 223 | "output_type": "execute_result" |
70 | 224 | } |
71 | 225 | ], |
72 | 226 | "source": [ |
73 | | - "from importlib_metadata import version\n", |
74 | | - "version(\"mdh\")" |
| 227 | + "r.as_euler('zyx', degrees=True)" |
| 228 | + ] |
| 229 | + }, |
| 230 | + { |
| 231 | + "cell_type": "code", |
| 232 | + "execution_count": 21, |
| 233 | + "metadata": {}, |
| 234 | + "outputs": [ |
| 235 | + { |
| 236 | + "data": { |
| 237 | + "text/plain": [ |
| 238 | + "array([-90.00999997, -44.99999992, 89.99999979])" |
| 239 | + ] |
| 240 | + }, |
| 241 | + "execution_count": 21, |
| 242 | + "metadata": {}, |
| 243 | + "output_type": "execute_result" |
| 244 | + } |
| 245 | + ], |
| 246 | + "source": [ |
| 247 | + "rr = [[ -0.00012341, 0.70710677, -0.70710678],\n", |
| 248 | + " [ 0.00012341, -0.70710677, -0.70710678],\n", |
| 249 | + " [ -0.99999998, -0.00017453, 0.]]\n", |
| 250 | + "\n", |
| 251 | + "r = R.from_matrix(rr)\n", |
| 252 | + "r.as_euler('zyx', degrees=True)" |
75 | 253 | ] |
76 | 254 | }, |
77 | 255 | { |
|
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