mppi_ee7500_proj_figure_eight.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MPPI control of a Differential Drive Robot on a Figure Eight path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[INFO] delta_t : 0.10[s] , sim_steps : 10000[steps], total_sim_time : 1000.00[s]\n",
      "Step : 0 time: --> 2.963139706000686 s, odometry: - [0.00155587 0.         0.0084477 ].\n",
      "Step : 1 time: --> 0.24531492799520493 s, odometry: - [9.14562804e-03 6.41175316e-05 1.77683193e-02].\n",
      "Step : 2 time: --> 0.24601014199852944 s, odometry: - [0.01988154 0.0002549  0.02515282].\n",
      "Step : 3 time: --> 0.24579450599849223 s, odometry: - [0.03646822 0.00067219 0.03195711].\n",
      "Step : 4 time: --> 0.2479166319966316 s, odometry: - [0.05868879 0.00138253 0.03762495].\n",
      "Step : 5 time: --> 0.24797073601186276 s, odometry: - [0.08503636 0.00237433 0.04165476].\n",
      "Step : 6 time: --> 0.24550789199769496 s, odometry: - [0.12083416 0.00386634 0.04527298].\n",
      "Step : 7 time: --> 0.24704877299070357 s, odometry: - [0.1645478  0.00584674 0.06234477].\n",
      "Step : 8 time: --> 0.24495178000628948 s, odometry: - [0.21136612 0.0087694  0.08607694].\n",
      "Step : 9 time: --> 0.24462828300893308 s, odometry: - [0.2585924  0.01284457 0.11459688].\n",
      "Step : 10 time: --> 0.2442200230062008 s, odometry: - [0.31172338 0.01896001 0.13886921].\n",
      "Step : 11 time: --> 0.24516247498989105 s, odometry: - [0.37638442 0.0279976  0.16368264].\n",
      "Step : 12 time: --> 0.24659476798772811 s, odometry: - [0.43742849 0.03807966 0.18449843].\n",
      "Step : 13 time: --> 0.24588696701824664 s, odometry: - [0.50364315 0.05043669 0.20744466].\n",
      "Step : 14 time: --> 0.24531815700232984 s, odometry: - [0.57367096 0.06517561 0.23860682].\n",
      "Step : 15 time: --> 0.24572155801951887 s, odometry: - [0.65536209 0.08504621 0.26997401].\n",
      "Step : 16 time: --> 0.24470371299982072 s, odometry: - [0.74004374 0.10848018 0.29521334].\n",
      "Step : 17 time: --> 0.24483453299105168 s, odometry: - [0.82057046 0.1329683  0.31378441].\n",
      "Step : 18 time: --> 0.24393070501089095 s, odometry: - [0.89861484 0.15829411 0.33362358].\n",
      "Step : 19 time: --> 0.24443830600380897 s, odometry: - [0.98704736 0.18894293 0.35872318].\n",
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      "Step : 24 time: --> 0.2450707060098648 s, odometry: - [1.53700414 0.42413491 0.47284681].\n",
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      "Step : 28 time: --> 0.24526797899603844 s, odometry: - [2.02399093 0.70739686 0.62283676].\n",
      "Step : 29 time: --> 0.24421813301742076 s, odometry: - [2.14634055 0.79526839 0.66429486].\n",
      "Step : 30 time: --> 0.24449106299877166 s, odometry: - [2.27305247 0.89448506 0.70692721].\n",
      "Step : 31 time: --> 0.24499418500065803 s, odometry: - [2.39804085 1.00125011 0.75321832].\n",
      "Step : 32 time: --> 0.2447021369934082 s, odometry: - [2.51679913 1.11260096 0.784947  ].\n",
      "Step : 33 time: --> 0.24470974500477313 s, odometry: - [2.64294384 1.2386319  0.81084212].\n",
      "Step : 34 time: --> 0.24556824600696564 s, odometry: - [2.77176415 1.37418025 0.83824004].\n",
      "Step : 35 time: --> 0.24555903799831869 s, odometry: - [2.90071201 1.51753024 0.86286007].\n",
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      "Step : 37 time: --> 0.2454185779839754 s, odometry: - [3.16530382 1.83224726 0.89868073].\n",
      "Step : 38 time: --> 0.2443868420124054 s, odometry: - [3.30180178 2.00379102 0.90962104].\n",
      "Step : 39 time: --> 0.25389791299402714 s, odometry: - [3.43525007 2.17532062 0.91415155].\n",
      "Step : 40 time: --> 0.2490387960076332 s, odometry: - [3.57234371 2.35319276 0.91470763].\n",
      "Step : 41 time: --> 0.2428591399937868 s, odometry: - [3.71514561 2.53868432 0.91953265].\n",
      "Step : 42 time: --> 0.24320731300115586 s, odometry: - [3.86490619 2.73516886 0.93320054].\n",
      "Step : 43 time: --> 0.2442218850106001 s, odometry: - [4.01793564 2.94173833 0.94479281].\n",
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      "Step : 45 time: --> 0.2429834100008011 s, odometry: - [4.33943635 3.3895552  0.95453931].\n",
      "Step : 46 time: --> 0.24437652498483659 s, odometry: - [4.50102965 3.61770622 0.95024815].\n",
      "Step : 47 time: --> 0.2425809829980135 s, odometry: - [4.66799025 3.85130351 0.94537572].\n",
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      "Step : 57 time: --> 0.24438373400270938 s, odometry: - [6.54451957 6.26185811 0.8706011 ].\n",
      "Step : 58 time: --> 0.24189507000148297 s, odometry: - [6.75131485 6.50727686 0.86853074].\n",
      "Step : 59 time: --> 0.24297459700703622 s, odometry: - [6.9571125  6.750488   0.86367955].\n",
      "Step : 60 time: --> 0.24446007001399994 s, odometry: - [7.16503157 6.99380259 0.85384865].\n",
      "Step : 61 time: --> 0.24529767198860644 s, odometry: - [7.3790603  7.23933793 0.84577008].\n",
      "Step : 62 time: --> 0.24612944900989533 s, odometry: - [7.59952217 7.48816622 0.83654343].\n",
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      "Step : 65 time: --> 0.245677398994565 s, odometry: - [8.29960652 8.25027071 0.8068289 ].\n",
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      "Step : 67 time: --> 0.24670980200171472 s, odometry: - [8.80634076 8.77090013 0.77934915].\n",
      "Step : 68 time: --> 0.24489876000583172 s, odometry: - [9.07078069 9.03216006 0.76849462].\n",
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      "Step : 70 time: --> 0.24600643299520017 s, odometry: - [9.61505056 9.55007047 0.743913  ].\n",
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      "Step : 345 time: --> 0.24711168499290942 s, odometry: - [99.09926564 13.21237833 -1.43897733].\n",
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      "Step : 512 time: --> 0.24969843399524688 s, odometry: - [ 71.98902278 -49.93020299  -3.09032247].\n",
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      "Step : 627 time: --> 0.24542854999005795 s, odometry: - [ 25.46875323 -24.60125839  -3.88488018].\n",
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      "Step : 629 time: --> 0.24545217099785804 s, odometry: - [ 24.73255959 -23.92448744  -3.88344643].\n",
      "Step : 630 time: --> 0.24568699099123478 s, odometry: - [ 24.36395465 -23.586663    -3.88442051].\n",
      "Step : 631 time: --> 0.24526297399401664 s, odometry: - [ 23.99567524 -23.24847625  -3.8837466 ].\n",
      "Step : 632 time: --> 0.24578852699697018 s, odometry: - [ 23.62765593 -22.91098521  -3.88340752].\n",
      "Step : 633 time: --> 0.24575902700424193 s, odometry: - [ 23.25903413 -22.5731717   -3.88475533].\n",
      "Step : 634 time: --> 0.24565369999408723 s, odometry: - [ 22.89086797 -22.23486166  -3.88598779].\n",
      "Step : 635 time: --> 0.24645605701208115 s, odometry: - [ 22.52311905 -21.89609813  -3.88565444].\n",
      "Step : 636 time: --> 0.2466236010044813 s, odometry: - [ 22.15525722 -21.55745721  -3.88687628].\n",
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      "Step : 640 time: --> 0.24672710399329661 s, odometry: - [ 20.68632496 -20.20041742  -3.88952152].\n",
      "Step : 641 time: --> 0.24659409500658513 s, odometry: - [ 20.31977543 -19.86035648  -3.88997445].\n",
      "Step : 642 time: --> 0.2464903799891472 s, odometry: - [ 19.95337996 -19.52012956  -3.88896307].\n",
      "Step : 643 time: --> 0.2458995710015297 s, odometry: - [ 19.58664058 -19.18027338  -3.88893471].\n",
      "Step : 644 time: --> 0.24570019599795342 s, odometry: - [ 19.21992413 -18.84045778  -3.88639291].\n",
      "Step : 645 time: --> 0.24655875000357627 s, odometry: - [ 18.85231248 -18.50154529  -3.88817445].\n",
      "Step : 646 time: --> 0.24717155799269677 s, odometry: - [ 18.48530519 -18.16197843  -3.88907432].\n",
      "Step : 647 time: --> 0.24770170100033284 s, odometry: - [ 18.11860362 -17.82208145  -3.89233356].\n",
      "Step : 648 time: --> 0.24716250100731849 s, odometry: - [ 17.7530118  -17.48099111  -3.89333562].\n",
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      "Step : 653 time: --> 0.24626798699796199 s, odometry: - [ 15.93355614 -15.76648166  -3.90218664].\n",
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      "Step : 656 time: --> 0.24686726701259612 s, odometry: - [ 14.84829642 -14.73100699  -3.90501066].\n",
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      "Step : 659 time: --> 0.25861330701410773 s, odometry: - [ 13.76762834 -13.69074466  -3.91136389].\n",
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      "Step : 661 time: --> 0.2466130990087986 s, odometry: - [ 13.0492008  -12.99514305  -3.90829544].\n",
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      "Step : 678 time: --> 0.24532491301000117 s, odometry: - [ 7.0087677  -7.01527454 -3.92256971].\n",
      "Step : 679 time: --> 0.24528624899685383 s, odometry: - [ 6.65365467 -6.6632877  -3.92126858].\n",
      "Step : 680 time: --> 0.24505794797837735 s, odometry: - [ 6.29808396 -6.31176321 -3.92042038].\n",
      "Step : 681 time: --> 0.24642182901501655 s, odometry: - [ 5.94221522 -5.96054043 -3.92165934].\n",
      "Step : 682 time: --> 0.24475920701026915 s, odometry: - [ 5.5867819  -5.60887702 -3.92210768].\n",
      "Step : 683 time: --> 0.24655630101263523 s, odometry: - [ 5.23150628 -5.25705428 -3.92528449].\n",
      "Step : 684 time: --> 0.2554148760139942 s, odometry: - [ 4.87735013 -4.90410469 -3.92818093].\n",
      "Step : 685 time: --> 0.2532538289874792 s, odometry: - [ 4.52421776 -4.55013078 -3.93248322].\n",
      "Step : 686 time: --> 0.2471148329973221 s, odometry: - [ 4.17261155 -4.19464087 -3.934882  ].\n",
      "Step : 687 time: --> 0.24626384100317955 s, odometry: - [ 3.82185909 -3.83830856 -3.93321627].\n",
      "Step : 688 time: --> 0.24569885101914407 s, odometry: - [ 3.47051357 -3.48256101 -3.93558712].\n",
      "Step : 689 time: --> 0.24530764600634575 s, odometry: - [ 3.12001245 -3.12598147 -3.934345  ].\n",
      "Step : 690 time: --> 0.24657608798146247 s, odometry: - [ 2.7690687  -2.76983756 -3.93370124].\n",
      "Step : 691 time: --> 0.24411926801502704 s, odometry: - [ 2.41789574 -2.41391966 -3.93393827].\n",
      "Step : 692 time: --> 0.2471802920103073 s, odometry: - [ 2.06680716 -2.05791852 -3.93762038].\n",
      "Step : 693 time: --> 0.24482433798909187 s, odometry: - [ 1.71703179 -1.70062706 -3.9374946 ].\n",
      "Step : 694 time: --> 0.2450171850025654 s, odometry: - [ 1.36721148 -1.34337959 -3.93094479].\n",
      "Step : 695 time: --> 0.24543107199668884 s, odometry: - [ 1.01505879 -0.98843102 -3.92884907].\n",
      "Step : 696 time: --> 0.24591266101598738 s, odometry: - [ 0.662163   -0.63422125 -3.92908796].\n",
      "Step : 697 time: --> 0.24674342200160027 s, odometry: - [ 0.30935184 -0.27992719 -3.92886055].\n",
      "Step : 698 time: --> 0.2459896340072155 s, odometry: - [-0.04353988  0.07428663 -3.93290186].\n",
      "Step : 699 time: --> 0.2449149499833584 s, odometry: - [-0.39499724  0.4299237  -3.93866144].\n",
      "Step : 700 time: --> 0.2467297499924898 s, odometry: - [-0.74440046  0.78757911 -3.9398703 ].\n",
      "Step : 701 time: --> 0.2465997989922762 s, odometry: - [-1.09337106  1.14565664 -3.93268503].\n",
      "Step : 702 time: --> 0.24475156098604203 s, odometry: - [-1.44490553  1.50121749 -3.92709088].\n",
      "Step : 703 time: --> 0.24465595398843287 s, odometry: - [-1.79842354  1.85480626 -3.92220918].\n",
      "Step : 704 time: --> 0.24599815198779107 s, odometry: - [-2.15366344  2.20666505 -3.92086615].\n",
      "Step : 705 time: --> 0.24422073501348496 s, odometry: - [-2.50937559  2.55804643 -3.92130511].\n",
      "Step : 706 time: --> 0.2449398580044508 s, odometry: - [-2.86493345  2.90958391 -3.92669975].\n",
      "Step : 707 time: --> 0.24408096899092196 s, odometry: - [-3.21858974  3.26303438 -3.92838754].\n",
      "Step : 708 time: --> 0.2455242419987917 s, odometry: - [-3.57164897  3.61708124 -3.92546907].\n",
      "Step : 709 time: --> 0.2465322059839964 s, odometry: - [-3.92573996  3.97009621 -3.9199791 ].\n",
      "Step : 710 time: --> 0.24645060600340365 s, odometry: - [-4.28176366  4.32116191 -3.91838054].\n",
      "Step : 711 time: --> 0.2449912170022726 s, odometry: - [-4.6383481   4.67165804 -3.91997601].\n",
      "Step : 712 time: --> 0.24575772601366044 s, odometry: - [-4.99437288  5.02272264 -3.91659229].\n",
      "Step : 713 time: --> 0.24586349000036717 s, odometry: - [-5.35158353  5.37258055 -3.91596144].\n",
      "Step : 714 time: --> 0.2455499820113182 s, odometry: - [-5.70901481  5.72221304 -3.91684566].\n",
      "Step : 715 time: --> 0.2457496140152216 s, odometry: - [-6.0661368   6.07216144 -3.91561352].\n",
      "Step : 716 time: --> 0.24474469600617885 s, odometry: - [-6.4236897   6.42166955 -3.91584502].\n",
      "Step : 717 time: --> 0.2457054780125618 s, odometry: - [-6.78116169  6.77126043 -3.91731486].\n",
      "Step : 718 time: --> 0.24520972000062466 s, odometry: - [-7.13811944  7.12137636 -3.91911123].\n",
      "Step : 719 time: --> 0.24605251199007033 s, odometry: - [-7.49444768  7.47213295 -3.917428  ].\n",
      "Step : 720 time: --> 0.24625284700095654 s, odometry: - [-7.85136582  7.82228926 -3.91570415].\n",
      "Step : 721 time: --> 0.24572897700965404 s, odometry: - [-8.20888705  8.17182977 -3.91153424].\n",
      "Step : 722 time: --> 0.24600620000064374 s, odometry: - [-8.56786271  8.51987643 -3.90735899].\n",
      "Step : 723 time: --> 0.24529651698470115 s, odometry: - [-8.92828843  8.86642123 -3.90968089].\n",
      "Step : 724 time: --> 0.2457951990067959 s, odometry: - [-9.28790853  9.21380198 -3.90296859].\n",
      "Step : 725 time: --> 0.24535772499442102 s, odometry: - [-9.64985223  9.55876104 -3.90489987].\n",
      "Step : 726 time: --> 0.24600740699470044 s, odometry: - [-10.01112905   9.90441847  -3.90246342].\n",
      "Step : 727 time: --> 0.2453396140038967 s, odometry: - [-10.37324698  10.24919464  -3.89707267].\n",
      "Step : 728 time: --> 0.24631425301730633 s, odometry: - [-10.73721823  10.59201373  -3.89401162].\n",
      "Step : 729 time: --> 0.24585954600572585 s, odometry: - [-11.10162971  10.93314842  -3.89604391].\n",
      "Step : 730 time: --> 0.24588073600828647 s, odometry: - [-11.46595345  11.27559289  -3.9013428 ].\n",
      "Step : 731 time: --> 0.2460243669897318 s, odometry: - [-11.82845751  11.61996305  -3.90726967].\n",
      "Step : 732 time: --> 0.24660957600176334 s, odometry: - [-12.18891418  11.96647567  -3.90604952].\n",
      "Step : 733 time: --> 0.24506964699923992 s, odometry: - [-12.54979337  12.31254821  -3.90643001].\n",
      "Step : 734 time: --> 0.24570024199783802 s, odometry: - [-12.91054086  12.65875804  -3.91053836].\n",
      "Step : 735 time: --> 0.24610119999945163 s, odometry: - [-13.26986296  13.00644702  -3.91110415].\n",
      "Step : 736 time: --> 0.24557835100591183 s, odometry: - [-13.62898829  13.35433925  -3.91267374].\n",
      "Step : 737 time: --> 0.2456726629883051 s, odometry: - [-13.98756712  13.70279473  -3.91807417].\n",
      "Step : 738 time: --> 0.2454408860206604 s, odometry: - [-14.34425893  14.05318159  -3.92429703].\n",
      "Step : 739 time: --> 0.24546913500130177 s, odometry: - [-14.69876343  14.40578131  -3.92919914].\n",
      "Step : 740 time: --> 0.2461176540106535 s, odometry: - [-15.0515352   14.76011459  -3.93046385].\n",
      "Step : 741 time: --> 0.24489987699687482 s, odometry: - [-15.40385856  15.11489375  -3.92360884].\n",
      "Step : 742 time: --> 0.2454534339904785 s, odometry: - [-15.75860564  15.46724941  -3.91972334].\n",
      "Step : 743 time: --> 0.2454121789932251 s, odometry: - [-16.11471911  15.81822405  -3.91595629].\n",
      "Step : 744 time: --> 0.24547712299227714 s, odometry: - [-16.47215219  16.1678547   -3.92042951].\n",
      "Step : 745 time: --> 0.24563671100139617 s, odometry: - [-16.82801773  16.51908072  -3.92303511].\n",
      "Step : 746 time: --> 0.24536332401633262 s, odometry: - [-17.1829669   16.8712328   -3.91851941].\n",
      "Step : 747 time: --> 0.24550303800404072 s, odometry: - [-17.53950267  17.22177844  -3.9128562 ].\n",
      "Step : 748 time: --> 0.24629627600312232 s, odometry: - [-17.89801791  17.57029934  -3.90954832].\n",
      "Step : 749 time: --> 0.24696641899645327 s, odometry: - [-18.25768406  17.91763241  -3.89838531].\n",
      "Step : 750 time: --> 0.24537240499258042 s, odometry: - [-18.62084957  18.26059329  -3.8951108 ].\n",
      "Step : 751 time: --> 0.24642041000723838 s, odometry: - [-18.98549269  18.60269766  -3.89173395].\n",
      "Step : 752 time: --> 0.2465541470050812 s, odometry: - [-19.35128896  18.94356873  -3.88940864].\n",
      "Step : 753 time: --> 0.24744029599428177 s, odometry: - [-19.71787688  19.28358828  -3.89222542].\n",
      "Step : 754 time: --> 0.2483889950066805 s, odometry: - [-20.08350558  19.62463909  -3.89023713].\n",
      "Step : 755 time: --> 0.24785647401213645 s, odometry: - [-20.44981167  19.96496225  -3.88716086].\n",
      "Step : 756 time: --> 0.24670102398097515 s, odometry: - [-20.81716294  20.30415694  -3.89141513].\n",
      "Step : 757 time: --> 0.24591803400218487 s, odometry: - [-21.18306788  20.64491137  -3.88529923].\n",
      "Step : 758 time: --> 0.24520855601131916 s, odometry: - [-21.55104997  20.9834216   -3.88409639].\n",
      "Step : 759 time: --> 0.24615518699586392 s, odometry: - [-21.91943897  21.32148896  -3.88890022].\n",
      "Step : 760 time: --> 0.2447886100113392 s, odometry: - [-22.28619972  21.6613221   -3.88538838].\n",
      "Step : 761 time: --> 0.24444706201553346 s, odometry: - [-22.65415163  21.99986513  -3.88549358].\n",
      "Step : 762 time: --> 0.24485124100744723 s, odometry: - [-23.02206793  22.33844687  -3.87848993].\n",
      "Step : 763 time: --> 0.24626186700165273 s, odometry: - [-23.3923465   22.67444357  -3.87395495].\n",
      "Step : 764 time: --> 0.2601390710026026 s, odometry: - [-23.76414499  23.00875762  -3.8747646 ].\n",
      "Step : 765 time: --> 0.24728662098944187 s, odometry: - [-24.13567268  23.34337259  -3.87249627].\n",
      "Step : 766 time: --> 0.24966186100244522 s, odometry: - [-24.50795843  23.67714394  -3.86713772].\n",
      "Step : 767 time: --> 0.24551624301075936 s, odometry: - [-24.88202736  24.00891561  -3.85988623].\n",
      "Step : 768 time: --> 0.24605338598787785 s, odometry: - [-25.25849228  24.33796601  -3.86173582].\n",
      "Step : 769 time: --> 0.24574485199153423 s, odometry: - [-25.63434794  24.66771216  -3.86467313].\n",
      "Step : 770 time: --> 0.2455978780090809 s, odometry: - [-26.00923341  24.99856089  -3.87295659].\n",
      "Step : 771 time: --> 0.24516187399625777 s, odometry: - [-26.38136548  25.33250358  -3.8738232 ].\n",
      "Step : 772 time: --> 0.24461494699120523 s, odometry: - [-26.75320801  25.66676864  -3.87205973].\n",
      "Step : 773 time: --> 0.245285399004817 s, odometry: - [-27.12563944  26.00037745  -3.86837574].\n",
      "Step : 774 time: --> 0.2451697470098734 s, odometry: - [-27.49929734  26.33261196  -3.86153794].\n",
      "Step : 775 time: --> 0.24655964401364328 s, odometry: - [-27.87521824  26.66228373  -3.86035226].\n",
      "Step : 776 time: --> 0.24734515400230886 s, odometry: - [-28.25152976  26.99150955  -3.86163836].\n",
      "Step : 777 time: --> 0.2451710730046034 s, odometry: - [-28.62741756  27.32121906  -3.86402675].\n",
      "Step : 778 time: --> 0.24523084799945355 s, odometry: - [-29.00251681  27.65182541  -3.86631818].\n",
      "Step : 779 time: --> 0.24558750300109386 s, odometry: - [-29.37685751  27.98329039  -3.86262303].\n",
      "Step : 780 time: --> 0.2452479150146246 s, odometry: - [-29.75242047  28.31336988  -3.8596966 ].\n",
      "Step : 781 time: --> 0.24519412100315094 s, odometry: - [-30.12894777  28.64234889  -3.85461945].\n",
      "Step : 782 time: --> 0.24566700300574304 s, odometry: - [-30.50714049  28.96941198  -3.85008149].\n",
      "Step : 783 time: --> 0.245043667986989 s, odometry: - [-30.88681351  29.29475549  -3.84200398].\n",
      "Step : 784 time: --> 0.24552724701166154 s, odometry: - [-31.26910208  29.61702161  -3.8385156 ].\n",
      "Step : 785 time: --> 0.2450430930107832 s, odometry: - [-31.6525125   29.9379522   -3.83579763].\n",
      "Step : 786 time: --> 0.2462691469937563 s, odometry: - [-32.03679379  30.25783951  -3.83535159].\n",
      "Step : 787 time: --> 0.2453885779976845 s, odometry: - [-32.42121773  30.57755538  -3.83664113].\n",
      "Step : 788 time: --> 0.24593543802201748 s, odometry: - [-32.80489874  30.89749128  -3.83263766].\n",
      "Step : 789 time: --> 0.24624850200116635 s, odometry: - [-33.19018894  31.21616268  -3.83294799].\n",
      "Step : 790 time: --> 0.2453974499851465 s, odometry: - [-33.57538024  31.53495362  -3.83474225].\n",
      "Step : 791 time: --> 0.2453069539964199 s, odometry: - [-33.95999892  31.85443519  -3.83276978].\n",
      "Step : 792 time: --> 0.24648220600187778 s, odometry: - [-34.34524701  32.17315749  -3.83101516].\n",
      "Step : 793 time: --> 0.2455491160005331 s, odometry: - [-34.73105375  32.49120333  -3.82843957].\n",
      "Step : 794 time: --> 0.2458044190108776 s, odometry: - [-35.11767837  32.80825444  -3.82600494].\n",
      "Step : 795 time: --> 0.2475894290059805 s, odometry: - [-35.50507374  33.12436332  -3.8249705 ].\n",
      "Step : 796 time: --> 0.24989921601116658 s, odometry: - [-35.8927959   33.4400713   -3.82237946].\n",
      "Step : 797 time: --> 0.24959749498963357 s, odometry: - [-36.28133477  33.75477362  -3.81744269].\n",
      "Step : 798 time: --> 0.24980456398427486 s, odometry: - [-36.67142251  34.06755397  -3.81005293].\n",
      "Step : 799 time: --> 0.24922329300642013 s, odometry: - [-37.06381095  34.37744317  -3.79968946].\n",
      "Step : 800 time: --> 0.24974392099678516 s, odometry: - [-37.45938979  34.68324928  -3.79501752].\n",
      "Step : 801 time: --> 0.2500266470015049 s, odometry: - [-37.85639302  34.98720395  -3.79167861].\n",
      "Step : 802 time: --> 0.2485748579800129 s, odometry: - [-38.25440891  35.28983137  -3.78724866].\n",
      "Step : 803 time: --> 0.249597618997097 s, odometry: - [-38.65376151  35.59069263  -3.78426719].\n",
      "Step : 804 time: --> 0.25015640999376776 s, odometry: - [-39.05400934  35.8903619   -3.77972005].\n",
      "Step : 805 time: --> 0.24908619698882103 s, odometry: - [-39.45561567  36.18820809  -3.77368281].\n",
      "Step : 806 time: --> 0.2497843529880047 s, odometry: - [-39.85901284  36.48362428  -3.77088196].\n",
      "Step : 807 time: --> 0.2549938350021839 s, odometry: - [-40.26323585  36.77790946  -3.76787242].\n",
      "Step : 808 time: --> 0.24958350901305676 s, odometry: - [-40.66834268  37.07097677  -3.76542764].\n",
      "Step : 809 time: --> 0.250043757006526 s, odometry: - [-41.07416479  37.36305282  -3.76219676].\n",
      "Step : 810 time: --> 0.24750403100252152 s, odometry: - [-41.48092844  37.65381618  -3.75658614].\n",
      "Step : 811 time: --> 0.24889570300281047 s, odometry: - [-41.88931704  37.94229278  -3.74820768].\n",
      "Step : 812 time: --> 0.24871707299351692 s, odometry: - [-42.30010827  38.22733763  -3.74449499].\n",
      "Step : 813 time: --> 0.24823037500679493 s, odometry: - [-42.71195495  38.51085538  -3.74200766].\n",
      "Step : 814 time: --> 0.24824705700576305 s, odometry: - [-43.12450556  38.79334785  -3.73535574].\n",
      "Step : 815 time: --> 0.247300602003932 s, odometry: - [-43.53892614  39.07308984  -3.73016372].\n",
      "Step : 816 time: --> 0.24495884200930595 s, odometry: - [-43.95479356  39.35067639  -3.72427683].\n",
      "Step : 817 time: --> 0.24573014798760415 s, odometry: - [-44.37228788  39.62580998  -3.72185741].\n",
      "Step : 818 time: --> 0.24548571698367597 s, odometry: - [-44.79044664  39.89993267  -3.71946844].\n",
      "Step : 819 time: --> 0.2452649910002947 s, odometry: - [-45.20925908  40.17305561  -3.71832288].\n",
      "Step : 820 time: --> 0.2459559080004692 s, odometry: - [-45.62838412  40.44569859  -3.71369966].\n",
      "Step : 821 time: --> 0.24618298500776292 s, odometry: - [-46.04876517  40.71640096  -3.7118679 ].\n",
      "Step : 822 time: --> 0.24497594799101352 s, odometry: - [-46.46964138  40.98633284  -3.70834926].\n",
      "Step : 823 time: --> 0.2452576610147953 s, odometry: - [-46.89146477  41.25478214  -3.70146318].\n",
      "Step : 824 time: --> 0.245775823995471 s, odometry: - [-47.31512671  41.52032039  -3.69610513].\n",
      "Step : 825 time: --> 0.24570786300301553 s, odometry: - [-47.74020533  41.78358483  -3.69056882].\n",
      "Step : 826 time: --> 0.24517581701278687 s, odometry: - [-48.16673494  42.04449189  -3.68408397].\n",
      "Step : 827 time: --> 0.2483533930182457 s, odometry: - [-48.59494751  42.3026275   -3.67676783].\n",
      "Step : 828 time: --> 0.2501058360040188 s, odometry: - [-49.02503716  42.55762336  -3.66992998].\n",
      "Step : 829 time: --> 0.24871496398746967 s, odometry: - [-49.45686037  42.8096724   -3.66204934].\n",
      "Step : 830 time: --> 0.24828435300290586 s, odometry: - [-49.89065646  43.0583106   -3.65674885].\n",
      "Step : 831 time: --> 0.24868663899600507 s, odometry: - [-50.32576435  43.30464599  -3.65162865].\n",
      "Step : 832 time: --> 0.24879001401364803 s, odometry: - [-50.76212781  43.54875033  -3.64647973].\n",
      "Step : 833 time: --> 0.2482082699984312 s, odometry: - [-51.19974236  43.79060463  -3.64447119].\n",
      "Step : 834 time: --> 0.24934325900673865 s, odometry: - [-51.6378418   44.03157949  -3.63825202].\n",
      "Step : 835 time: --> 0.24886411599814892 s, odometry: - [-52.07743143  44.26982508  -3.63246764].\n",
      "Step : 836 time: --> 0.24947847399115564 s, odometry: - [-52.51839179  44.50552395  -3.62496393].\n",
      "Step : 837 time: --> 0.24864249201118946 s, odometry: - [-52.96110834  44.73790737  -3.61738846].\n",
      "Step : 838 time: --> 0.24960775299370289 s, odometry: - [-53.40494519  44.96660709  -3.61094977].\n",
      "Step : 839 time: --> 0.2480484070032835 s, odometry: - [-53.85087482  45.1927636   -3.60521858].\n",
      "Step : 840 time: --> 0.24557363098859786 s, odometry: - [-54.29809327  45.4163607   -3.59749909].\n",
      "Step : 841 time: --> 0.24520423699915408 s, odometry: - [-54.74702442  45.63649888  -3.5892686 ].\n",
      "Step : 842 time: --> 0.24763314999639988 s, odometry: - [-55.1977522   45.85293472  -3.58008723].\n",
      "Step : 843 time: --> 0.24703805300593376 s, odometry: - [-55.65044813  46.06522319  -3.56868083].\n",
      "Step : 844 time: --> 0.24753962498903276 s, odometry: - [-56.10498504  46.27208359  -3.5622211 ].\n",
      "Step : 845 time: --> 0.24688856799900533 s, odometry: - [-56.55849761  46.47495179  -3.55287142].\n",
      "Step : 846 time: --> 0.24787777599692346 s, odometry: - [-57.01022228  46.67197259  -3.54446889].\n",
      "Step : 847 time: --> 0.24918215999007226 s, odometry: - [-57.46068135  46.86395271  -3.5355603 ].\n",
      "Step : 848 time: --> 0.24745485600829126 s, odometry: - [-57.91057531  47.05097388  -3.5250956 ].\n",
      "Step : 849 time: --> 0.2467732309997082 s, odometry: - [-58.36303218  47.23353127  -3.51337695].\n",
      "Step : 850 time: --> 0.24772982400655746 s, odometry: - [-58.81179375  47.40851117  -3.50346379].\n",
      "Step : 851 time: --> 0.24774715700745584 s, odometry: - [-59.26324266  47.57940291  -3.49130469].\n",
      "Step : 852 time: --> 0.24826615300774574 s, odometry: - [-59.71162954  47.74293059  -3.48064904].\n",
      "Step : 853 time: --> 0.24963645300269127 s, odometry: - [-60.15909617  47.90074113  -3.46923033].\n",
      "Step : 854 time: --> 0.24971623800694942 s, odometry: - [-60.60571972  48.0525429   -3.45814958].\n",
      "Step : 855 time: --> 0.24983957500755788 s, odometry: - [-61.04751069  48.1972615   -3.44745219].\n",
      "Step : 856 time: --> 0.2483770010024309 s, odometry: - [-61.48721517  48.33610619  -3.43577853].\n",
      "Step : 857 time: --> 0.24037815199792384 s, odometry: - [-61.92799087  48.46965116  -3.42372244].\n",
      "Step : 858 time: --> 0.2408692479878664 s, odometry: - [-62.36522549  48.5963887   -3.41048335].\n",
      "Step : 859 time: --> 0.24092922399938108 s, odometry: - [-62.79964836  48.71610011  -3.39814533].\n",
      "Step : 860 time: --> 0.2408119540065527 s, odometry: - [-63.23218324  48.82956855  -3.38500765].\n",
      "Step : 861 time: --> 0.24218577998876573 s, odometry: - [-63.66083521  48.93601966  -3.37288786].\n",
      "Step : 862 time: --> 0.24110851299762726 s, odometry: - [-64.08666587  49.03630703  -3.35962008].\n",
      "Step : 863 time: --> 0.2404588399976492 s, odometry: - [-64.51098865  49.13031537  -3.34708079].\n",
      "Step : 864 time: --> 0.2417523310035467 s, odometry: - [-64.93233107  49.21813582  -3.33458007].\n",
      "Step : 865 time: --> 0.2426915580034256 s, odometry: - [-65.35341393  49.30042364  -3.32418675].\n",
      "Step : 866 time: --> 0.24202449299395085 s, odometry: - [-65.77525124  49.37831623  -3.31095631].\n",
      "Step : 867 time: --> 0.2515720050036907 s, odometry: - [-66.1928247   49.44972205  -3.29843948].\n",
      "Step : 868 time: --> 0.24036662401258946 s, odometry: - [-66.60966116  49.51564298  -3.28507318].\n",
      "Step : 869 time: --> 0.24109842199087142 s, odometry: - [-67.02810876  49.57609749  -3.26990794].\n",
      "Step : 870 time: --> 0.24031252698600292 s, odometry: - [-67.44580782  49.62999077  -3.25473287].\n",
      "Step : 871 time: --> 0.24082495498657228 s, odometry: - [-67.86387424  49.67749375  -3.23881769].\n",
      "Step : 872 time: --> 0.24125412000715732 s, odometry: - [-68.27915294  49.71799694  -3.2255986 ].\n",
      "Step : 873 time: --> 0.24098328399658203 s, odometry: - [-68.69033287  49.75261999  -3.20955758].\n",
      "Step : 874 time: --> 0.24031282199919224 s, odometry: - [-69.1016055   49.78061522  -3.19405999].\n",
      "Step : 875 time: --> 0.24062520399689674 s, odometry: - [-69.51146202  49.80213905  -3.17814407].\n",
      "Step : 876 time: --> 0.24178105199337005 s, odometry: - [-69.91755925  49.8169891   -3.16190504].\n",
      "Step : 877 time: --> 0.24017103300988674 s, odometry: - [-70.32257823  49.82521713  -3.14535221].\n",
      "Step : 878 time: --> 0.23995622800290584 s, odometry: - [-70.72131561  49.82671621  -3.12896817].\n",
      "Step : 879 time: --> 0.24061761300265788 s, odometry: - [-71.1140168   49.8217583   -3.11353822].\n",
      "Step : 880 time: --> 0.24047137200832366 s, odometry: - [-71.50544028  49.81077425  -3.09923763].\n",
      "Step : 881 time: --> 0.24102816899120807 s, odometry: - [-71.89492318  49.79426782  -3.08386089].\n",
      "Step : 882 time: --> 0.2399452219903469 s, odometry: - [-72.28383188  49.77179046  -3.06757635].\n",
      "Step : 883 time: --> 0.23919912400841714 s, odometry: - [-72.66903801  49.74322675  -3.05282426].\n",
      "Step : 884 time: --> 0.2386116810142994 s, odometry: - [-73.05066041  49.70926148  -3.0378335 ].\n",
      "Step : 885 time: --> 0.23956334201991558 s, odometry: - [-73.42940442  49.66982168  -3.02091741].\n",
      "Step : 886 time: --> 0.24027097399532796 s, odometry: - [-73.80794404  49.62391828  -3.00560851].\n",
      "Step : 887 time: --> 0.240885527998209 s, odometry: - [-74.18379534  49.57249109  -2.9870598 ].\n",
      "Step : 888 time: --> 0.24050161799788475 s, odometry: - [-74.56000174  49.5138876   -2.97064076].\n",
      "Step : 889 time: --> 0.24072259099781512 s, odometry: - [-74.93442089  49.44924903  -2.95669115].\n",
      "Step : 890 time: --> 0.23998462599515916 s, odometry: - [-75.30703628  49.37955583  -2.93959713].\n",
      "Step : 891 time: --> 0.24086688600480557 s, odometry: - [-75.6746966   49.30426326  -2.92395897].\n",
      "Step : 892 time: --> 0.2409052609950304 s, odometry: - [-76.04172304  49.22310048  -2.90767392].\n",
      "Step : 893 time: --> 0.24087541000545024 s, odometry: - [-76.40736269  49.13597558  -2.88871076].\n",
      "Step : 894 time: --> 0.24256040400266649 s, odometry: - [-76.77279641  49.0415424   -2.87121739].\n",
      "Step : 895 time: --> 0.23990717101097106 s, odometry: - [-77.13665616  48.94069424  -2.8539828 ].\n",
      "Step : 896 time: --> 0.2408410510122776 s, odometry: - [-77.49800425  48.83380326  -2.83879763].\n",
      "Step : 897 time: --> 0.240180555999279 s, odometry: - [-77.85542738  48.72214378  -2.82088641].\n",
      "Step : 898 time: --> 0.24244354398548604 s, odometry: - [-78.21140357  48.60389796  -2.80202673].\n",
      "Step : 899 time: --> 0.24261203800141812 s, odometry: - [-78.56345141  48.47953757  -2.7818387 ].\n",
      "Step : 900 time: --> 0.24123589600622655 s, odometry: - [-78.91312621  48.3480172   -2.76352406].\n",
      "Step : 901 time: --> 0.24010686899721623 s, odometry: - [-79.26062891  48.20999784  -2.74612319].\n",
      "Step : 902 time: --> 0.24020144699513912 s, odometry: - [-79.60229529  48.06736477  -2.72701681].\n",
      "Step : 903 time: --> 0.23983895799517632 s, odometry: - [-79.94068942  47.91844349  -2.70975005].\n",
      "Step : 904 time: --> 0.24210231000185012 s, odometry: - [-80.27340938  47.76510847  -2.69464856].\n",
      "Step : 905 time: --> 0.23992059499025345 s, odometry: - [-80.60640488  47.60550652  -2.67771843].\n",
      "Step : 906 time: --> 0.24136149699985981 s, odometry: - [-80.93842879  47.4394005   -2.66093524].\n",
      "Step : 907 time: --> 0.2393374049961567 s, odometry: - [-81.26732995  47.26789607  -2.64241162].\n",
      "Step : 908 time: --> 0.240011524990201 s, odometry: - [-81.59295645  47.09035162  -2.62459031].\n",
      "Step : 909 time: --> 0.2400828420072794 s, odometry: - [-81.91703046  46.90608693  -2.60489329].\n",
      "Step : 910 time: --> 0.23983327600359916 s, odometry: - [-82.23681571  46.7158301   -2.58834399].\n",
      "Step : 911 time: --> 0.24051604199409485 s, odometry: - [-82.55387098  46.52002185  -2.57337384].\n",
      "Step : 912 time: --> 0.24102473200857638 s, odometry: - [-82.87288383  46.31634539  -2.55556877].\n",
      "Step : 913 time: --> 0.24105347698926927 s, odometry: - [-83.186941    46.1078704   -2.53743956].\n",
      "Step : 914 time: --> 0.240538139000535 s, odometry: - [-83.49981742  45.89190709  -2.51802574].\n",
      "Step : 915 time: --> 0.240156912997365 s, odometry: - [-83.81103764  45.66804401  -2.50209481].\n",
      "Step : 916 time: --> 0.24044447800517083 s, odometry: - [-84.11955762  45.43857809  -2.48193237].\n",
      "Step : 917 time: --> 0.2406146350055933 s, odometry: - [-84.42122732  45.20461492  -2.46717034].\n",
      "Step : 918 time: --> 0.24012435801327228 s, odometry: - [-84.71922855  44.96636962  -2.45143419].\n",
      "Step : 919 time: --> 0.24089098198711872 s, odometry: - [-85.01434629  44.72271966  -2.43756013].\n",
      "Step : 920 time: --> 0.24122770100831986 s, odometry: - [-85.30883068  44.47264196  -2.42013877].\n",
      "Step : 921 time: --> 0.24135270300507544 s, odometry: - [-85.60045304  44.21611825  -2.40294108].\n",
      "Step : 922 time: --> 0.2418990029990673 s, odometry: - [-85.88660449  43.95554305  -2.38958696].\n",
      "Step : 923 time: --> 0.24103010499477387 s, odometry: - [-86.17002258  43.69044797  -2.37597221].\n",
      "Step : 924 time: --> 0.24065772700309754 s, odometry: - [-86.44824433  43.42301935  -2.36417762].\n",
      "Step : 925 time: --> 0.240747721016407 s, odometry: - [-86.72601856  43.1496451   -2.34979872].\n",
      "Step : 926 time: --> 0.24011072099208833 s, odometry: - [-87.00393912  42.86814657  -2.33583491].\n",
      "Step : 927 time: --> 0.24065044701099395 s, odometry: - [-87.27589297  42.58488726  -2.32398283].\n",
      "Step : 928 time: --> 0.24080871199071407 s, odometry: - [-87.54585672  42.29694625  -2.30934138].\n",
      "Step : 929 time: --> 0.23983186000585557 s, odometry: - [-87.81372972  42.00271776  -2.29585905].\n",
      "Step : 930 time: --> 0.23969621801376342 s, odometry: - [-88.07936714  41.7029233   -2.28310311].\n",
      "Step : 931 time: --> 0.24096691200137138 s, odometry: - [-88.34151881  41.39934808  -2.26878913].\n",
      "Step : 932 time: --> 0.24136023999750614 s, odometry: - [-88.59889473  41.09253286  -2.25521295].\n",
      "Step : 933 time: --> 0.23986812399327756 s, odometry: - [-88.85209753  40.78223242  -2.24147449].\n",
      "Step : 934 time: --> 0.24572463999688626 s, odometry: - [-89.10322522  40.46569499  -2.22813242].\n",
      "Step : 935 time: --> 0.24291699400544167 s, odometry: - [-89.35081762  40.14491514  -2.21642205].\n",
      "Step : 936 time: --> 0.2424470480084419 s, odometry: - [-89.59404317  39.8220458   -2.20458482].\n",
      "Step : 937 time: --> 0.2416812929958105 s, odometry: - [-89.83557052  39.49340734  -2.18850969].\n",
      "Step : 938 time: --> 0.24237147299945355 s, odometry: - [-90.07259245  39.159791    -2.17409992].\n",
      "Step : 939 time: --> 0.24220385500788688 s, odometry: - [-90.30310024  38.82523572  -2.16137177].\n",
      "Step : 940 time: --> 0.2404702830016613 s, odometry: - [-90.52980587  38.48706566  -2.15295969].\n",
      "Step : 941 time: --> 0.23946196998655797 s, odometry: - [-90.75503542  38.1449092   -2.14308448].\n",
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      "Step : 943 time: --> 0.2402125830054283 s, odometry: - [-91.20033557  37.44568173  -2.12308137].\n",
      "Step : 944 time: --> 0.2399965550005436 s, odometry: - [-91.42003235  37.08917791  -2.11347855].\n",
      "Step : 945 time: --> 0.2403620890080929 s, odometry: - [-91.63669277  36.72992228  -2.1022755 ].\n",
      "Step : 946 time: --> 0.24014781598746776 s, odometry: - [-91.84828912  36.37000683  -2.0911293 ].\n",
      "Step : 947 time: --> 0.2406157950013876 s, odometry: - [-92.05769803  36.00454882  -2.08220709].\n",
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      "Step : 949 time: --> 0.23943183000385762 s, odometry: - [-92.47184051  35.25695547  -2.05871644].\n",
      "Step : 950 time: --> 0.24001945300400257 s, odometry: - [-92.67273808  34.87841732  -2.04704368].\n",
      "Step : 951 time: --> 0.2400224170088768 s, odometry: - [-92.87014458  34.49573561  -2.03542422].\n",
      "Step : 952 time: --> 0.23971172498166562 s, odometry: - [-93.06353061  34.10990957  -2.02523178].\n",
      "Step : 953 time: --> 0.24046678000688554 s, odometry: - [-93.25380919  33.72042326  -2.0161154 ].\n",
      "Step : 954 time: --> 0.23973677299916743 s, odometry: - [-93.44024307  33.329818    -2.00732013].\n",
      "Step : 955 time: --> 0.24005541600286961 s, odometry: - [-93.62606436  32.93152211  -1.99956167].\n",
      "Step : 956 time: --> 0.24149239000678063 s, odometry: - [-93.80936409  32.53054051  -1.99142501].\n",
      "Step : 957 time: --> 0.23917117699980736 s, odometry: - [-93.99045855  32.12570347  -1.98552659].\n",
      "Step : 958 time: --> 0.24000316099822522 s, odometry: - [-94.16893953  31.72031057  -1.97691856].\n",
      "Step : 959 time: --> 0.24196478998661042 s, odometry: - [-94.34505067  31.31077707  -1.97065165].\n",
      "Step : 960 time: --> 0.24009914000332355 s, odometry: - [-94.51897256  30.89924714  -1.96185784].\n",
      "Step : 961 time: --> 0.23983862799406053 s, odometry: - [-94.68980204  30.48491049  -1.95340903].\n",
      "Step : 962 time: --> 0.24069918599724768 s, odometry: - [-94.85808522  30.06675889  -1.94409303].\n",
      "Step : 963 time: --> 0.24173169501125813 s, odometry: - [-95.02476112  29.64119691  -1.93450773].\n",
      "Step : 964 time: --> 0.242472437992692 s, odometry: - [-95.18810041  29.21208619  -1.92509318].\n",
      "Step : 965 time: --> 0.24264553101360797 s, odometry: - [-95.34653068  28.78378697  -1.91557066].\n",
      "Step : 966 time: --> 0.24353172799944878 s, odometry: - [-95.50170509  28.351688    -1.90984886].\n",
      "Step : 967 time: --> 0.24324688898026944 s, odometry: - [-95.65556528  27.91541707  -1.90159234].\n",
      "Step : 968 time: --> 0.24405278800427913 s, odometry: - [-95.80612295  27.47700325  -1.89601448].\n",
      "Step : 969 time: --> 0.24187908798456192 s, odometry: - [-95.95501539  27.03543579  -1.89270397].\n",
      "Step : 970 time: --> 0.2387864789813757 s, odometry: - [-96.10367518  26.58968984  -1.88630433].\n",
      "Step : 971 time: --> 0.2399673040062189 s, odometry: - [-96.24973457  26.1422197   -1.88043808].\n",
      "Step : 972 time: --> 0.25452037301659586 s, odometry: - [-96.39307907  25.69417367  -1.87098186].\n",
      "Step : 973 time: --> 0.2389716099947691 s, odometry: - [-96.53325178  25.24133103  -1.86226067].\n",
      "Step : 974 time: --> 0.23921105101704598 s, odometry: - [-96.66949999  24.78718278  -1.85355024].\n",
      "Step : 975 time: --> 0.23685414001345634 s, odometry: - [-96.80284888  24.32821101  -1.84840261].\n",
      "Step : 976 time: --> 0.23962227101624012 s, odometry: - [-96.93446618  23.86633833  -1.84044827].\n",
      "Step : 977 time: --> 0.23938274699449538 s, odometry: - [-97.06343075  23.39972367  -1.83450025].\n",
      "Step : 978 time: --> 0.23896649499237538 s, odometry: - [-97.18970662  22.93202055  -1.82602691].\n",
      "Step : 979 time: --> 0.23898807699978353 s, odometry: - [-97.31172512  22.46437526  -1.8194498 ].\n",
      "Step : 980 time: --> 0.23825055399537087 s, odometry: - [-97.43144249  21.99287642  -1.81232655].\n",
      "Step : 981 time: --> 0.23925472500920295 s, odometry: - [-97.54860366  21.51726727  -1.80309453].\n",
      "Step : 982 time: --> 0.23873542401194572 s, odometry: - [-97.66156662  21.03976167  -1.7973583 ].\n",
      "Step : 983 time: --> 0.24050212800502777 s, odometry: - [-97.77191353  20.56107424  -1.79001223].\n",
      "Step : 984 time: --> 0.23953246900439262 s, odometry: - [-97.87853153  20.08252939  -1.78602682].\n",
      "Step : 985 time: --> 0.2389915819913149 s, odometry: - [-97.98410963  19.59959242  -1.78072285].\n",
      "Step : 986 time: --> 0.2399384069889784 s, odometry: - [-98.08711063  19.11616857  -1.77556157].\n",
      "Step : 987 time: --> 0.2398172330111265 s, odometry: - [-98.18737523  18.633375    -1.76791307].\n",
      "Step : 988 time: --> 0.2394224219918251 s, odometry: - [-98.28446646  18.14721407  -1.76292641].\n",
      "Step : 989 time: --> 0.24056007899343967 s, odometry: - [-98.37939766  17.65921022  -1.75656162].\n",
      "Step : 990 time: --> 0.23820111399888994 s, odometry: - [-98.47129631  17.17021084  -1.75041365].\n",
      "Step : 991 time: --> 0.23750212702155113 s, odometry: - [-98.56051455  16.67885123  -1.74449723].\n",
      "Step : 992 time: --> 0.23807488000392915 s, odometry: - [-98.64692891  16.18637528  -1.74030036].\n",
      "Step : 993 time: --> 0.23899552001059055 s, odometry: - [-98.73127567  15.69354101  -1.73583348].\n",
      "Step : 994 time: --> 0.24177384100854396 s, odometry: - [-98.81342016  15.20033488  -1.72973042].\n",
      "Step : 995 time: --> 0.24476672899723054 s, odometry: - [-98.89255307  14.70663661  -1.72308637].\n",
      "Step : 996 time: --> 0.24136977399885653 s, odometry: - [-98.96840411  14.21242348  -1.71944137].\n",
      "Step : 997 time: --> 0.2420141310095787 s, odometry: - [-99.04233336  13.71873763  -1.71424972].\n",
      "Step : 998 time: --> 0.2420035389959812 s, odometry: - [-99.11381431  13.22387353  -1.7075437 ].\n",
      "Step : 999 time: --> 0.24169604700803757 s, odometry: - [-99.1819751   12.72854121  -1.70304108].\n",
      "Step : 1000 time: --> 0.24155698899924755 s, odometry: - [-99.24790491  12.23290701  -1.69720624].\n",
      "Step : 1001 time: --> 0.2403258540034294 s, odometry: - [-99.31094167  11.73689656  -1.69068   ].\n",
      "Step : 1002 time: --> 0.23976492097973823 s, odometry: - [-99.37074003  11.24048528  -1.68424002].\n",
      "Step : 1003 time: --> 0.2402704939842224 s, odometry: - [-99.42734029  10.7436992   -1.67854714].\n",
      "Step : 1004 time: --> 0.2393814110159874 s, odometry: - [-99.48111151  10.24659896  -1.67253956].\n",
      "Step : 1005 time: --> 0.24000664399564267 s, odometry: - [-99.5318954    9.74918465  -1.66463847].\n",
      "Step : 1006 time: --> 0.2389511869996786 s, odometry: - [-99.57874764   9.25138462  -1.65730397].\n",
      "Step : 1007 time: --> 0.23941655299067496 s, odometry: - [-99.62194753   8.75325434  -1.65292029].\n",
      "Step : 1008 time: --> 0.23989297199249268 s, odometry: - [-99.66296338   8.25493948  -1.65012056].\n",
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      "Step : 1064 time: --> 0.2438581539839506 s, odometry: - [-97.93676    -19.58756469  -1.345696  ].\n",
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      "Step : 1112 time: --> 0.24356341698765754 s, odometry: - [-88.97902363 -40.37321385  -0.89939737].\n",
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      "Step : 1125 time: --> 0.2472164639979601 s, odometry: - [-85.40413288 -44.19229687  -0.72013313].\n",
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      "Step : 1131 time: --> 0.2385096180140972 s, odometry: - [-83.60225623 -45.65273307  -0.62104308].\n",
      "Step : 1132 time: --> 0.2370146780014038 s, odometry: - [-83.28938045 -45.87659096  -0.60552027].\n",
      "Step : 1133 time: --> 0.23605161099135877 s, odometry: - [-82.97368153 -46.09514036  -0.58775287].\n",
      "Step : 1134 time: --> 0.23559147198498248 s, odometry: - [-82.65782557 -46.30559708  -0.56990879].\n",
      "Step : 1135 time: --> 0.23470675799250604 s, odometry: - [-82.33460699 -46.51272843  -0.55107217].\n",
      "Step : 1136 time: --> 0.2347522860020399 s, odometry: - [-82.00777165 -46.71359535  -0.53264147].\n",
      "Step : 1137 time: --> 0.2342102710008621 s, odometry: - [-81.68393981 -46.90448476  -0.5155649 ].\n",
      "Step : 1138 time: --> 0.23323082000017167 s, odometry: - [-81.35948134 -47.08835137  -0.50060025].\n",
      "Step : 1139 time: --> 0.23296024899184703 s, odometry: - [-81.03674249 -47.26491603  -0.48473601].\n",
      "Step : 1140 time: --> 0.23242001900076867 s, odometry: - [-80.70835309 -47.4378608   -0.47144002].\n",
      "Step : 1141 time: --> 0.230949486002326 s, odometry: - [-80.37833228 -47.60609841  -0.45930404].\n",
      "Step : 1142 time: --> 0.23150298799574376 s, odometry: - [-80.04688658 -47.77002558  -0.44495826].\n",
      "Step : 1143 time: --> 0.22978085099160672 s, odometry: - [-79.71550164 -47.92804713  -0.42918788].\n",
      "Step : 1144 time: --> 0.22901719999313355 s, odometry: - [-79.3769954  -48.0829606   -0.40924068].\n",
      "Step : 1145 time: --> 0.2278580270111561 s, odometry: - [-79.03785434 -48.23005583  -0.39563584].\n",
      "Step : 1146 time: --> 0.2275455129891634 s, odometry: - [-78.69553655 -48.37302772  -0.37983939].\n",
      "Step : 1147 time: --> 0.22589529299736022 s, odometry: - [-78.34464508 -48.5131129   -0.36651932].\n",
      "Step : 1148 time: --> 0.22559451299905778 s, odometry: - [-77.99175659 -48.64857417  -0.35588296].\n",
      "Step : 1149 time: --> 0.22425302900373936 s, odometry: - [-77.63726308 -48.78034286  -0.34216351].\n",
      "Step : 1150 time: --> 0.22347084198892117 s, odometry: - [-77.28431608 -48.90605305  -0.32173837].\n",
      "Step : 1151 time: --> 0.22331019899249077 s, odometry: - [-76.92773545 -49.02490843  -0.29843439].\n",
      "Step : 1152 time: --> 0.2230694949924946 s, odometry: - [-76.57118577 -49.13459084  -0.27831179].\n",
      "Step : 1153 time: --> 0.22259085300564765 s, odometry: - [-76.20740137 -49.23853401  -0.25926036].\n",
      "Step : 1154 time: --> 0.2221573890000582 s, odometry: - [-75.84038473 -49.33587773  -0.24788777].\n",
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      "Step : 1156 time: --> 0.2185086669921875 s, odometry: - [-75.10254897 -49.51615166  -0.21703554].\n",
      "Step : 1157 time: --> 0.2180421379953623 s, odometry: - [-74.73106632 -49.59806684  -0.19983042].\n",
      "Step : 1158 time: --> 0.21798245300352573 s, odometry: - [-74.35665206 -49.67389827  -0.17905982].\n",
      "Step : 1159 time: --> 0.2171639470010996 s, odometry: - [-73.98439828 -49.74127561  -0.15610102].\n",
      "Step : 1160 time: --> 0.21697638100385666 s, odometry: - [-73.60641828 -49.80076264  -0.13762699].\n",
      "Step : 1161 time: --> 0.2160092389881611 s, odometry: - [-73.2233844  -49.85381381  -0.11857336].\n",
      "Step : 1162 time: --> 0.21514602600038052 s, odometry: - [-72.83687495 -49.89985954  -0.102292  ].\n",
      "Step : 1163 time: --> 0.2153788949996233 s, odometry: - [-72.45257099 -49.93930845  -0.08746398].\n",
      "Step : 1164 time: --> 0.21487988199293614 s, odometry: - [-7.20653208e+01 -4.99732655e+01 -6.88304033e-02].\n",
      "Step : 1165 time: --> 0.21348028400540353 s, odometry: - [-7.16723044e+01 -5.00003598e+01 -5.16877280e-02].\n",
      "Step : 1166 time: --> 0.2114562360048294 s, odometry: - [-7.12807437e+01 -5.00206167e+01 -2.92628827e-02].\n",
      "Step : 1167 time: --> 0.21186029301583767 s, odometry: - [-7.08885858e+01 -5.00320957e+01 -1.09787046e-02].\n",
      "Step : 1168 time: --> 0.21029592099785804 s, odometry: - [-7.04950855e+01 -5.00364160e+01  8.52606379e-03].\n",
      "Step : 1169 time: --> 0.210145156994462 s, odometry: - [-7.00960621e+01 -5.00330138e+01  2.59274728e-02].\n",
      "Step : 1170 time: --> 0.20926890799403192 s, odometry: - [-6.96952925e+01 -5.00226205e+01  4.09500991e-02].\n",
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      "Step : 1173 time: --> 0.206995561003685 s, odometry: - [-68.48381743 -49.95397307   0.08596831].\n",
      "Step : 1174 time: --> 0.2058311239928007 s, odometry: - [-68.08232057 -49.91937178   0.10055332].\n",
      "Step : 1175 time: --> 0.20522994600236416 s, odometry: - [-67.68154737 -49.87893634   0.11895998].\n",
      "Step : 1176 time: --> 0.20479973700642587 s, odometry: - [-67.27782402 -49.83068157   0.1305631 ].\n",
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      "Step : 1180 time: --> 0.2021145219951868 s, odometry: - [-65.64777237 -49.57850233   0.19032825].\n",
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      "Step : 1182 time: --> 0.2000842619985342 s, odometry: - [-64.83168104 -49.4156631    0.21537487].\n",
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      "Step : 1193 time: --> 0.19415109698474406 s, odometry: - [-60.25302185 -48.1147237    0.34501574].\n",
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      "Step : 1199 time: --> 0.18816152600944042 s, odometry: - [-57.72634212 -47.14044541   0.39741028].\n",
      "Step : 1200 time: --> 0.18729041799902915 s, odometry: - [-57.29975181 -46.96138673   0.40667587].\n",
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      "Step : 1202 time: --> 0.18618522898852824 s, odometry: - [-56.45392912 -46.59281423   0.41951041].\n",
      "Step : 1203 time: --> 0.1849916719943285 s, odometry: - [-56.03012714 -46.40380471   0.42651727].\n",
      "Step : 1204 time: --> 0.1856324419826269 s, odometry: - [-55.60448944 -46.21038963   0.43494556].\n",
      "Step : 1205 time: --> 0.18414944599568844 s, odometry: - [-55.17606464 -46.0113347    0.44452784].\n",
      "Step : 1206 time: --> 0.18326691599190234 s, odometry: - [-54.74497356 -45.80599578   0.45259471].\n",
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      "Step : 1210 time: --> 0.18115536600351334 s, odometry: - [-53.01572262 -44.9426562    0.4792488 ].\n",
      "Step : 1211 time: --> 0.17966118800640107 s, odometry: - [-52.58505517 -44.7188571    0.48409838].\n",
      "Step : 1212 time: --> 0.1784509280025959 s, odometry: - [-52.15495601 -44.49269754   0.49135971].\n",
      "Step : 1213 time: --> 0.17734621998667716 s, odometry: - [-51.72572849 -44.26300246   0.50129636].\n",
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      "Step : 1222 time: --> 0.17260828000307082 s, odometry: - [-47.97520656 -42.11492717   0.55526121].\n",
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      "Step : 1224 time: --> 0.17127918100357056 s, odometry: - [-47.14825947 -41.59844612   0.56726748].\n",
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      "Step : 1226 time: --> 0.1709242060035467 s, odometry: - [-46.32324952 -41.06902744   0.57562761].\n",
      "Step : 1227 time: --> 0.16988828898966313 s, odometry: - [-45.9087075  -40.80001576   0.57928384].\n",
      "Step : 1228 time: --> 0.16829101200401783 s, odometry: - [-45.4944049  -40.52900164   0.58465765].\n",
      "Step : 1229 time: --> 0.1662119089961052 s, odometry: - [-45.07845928 -40.25370978   0.59263092].\n",
      "Step : 1230 time: --> 0.165483486995101 s, odometry: - [-44.66499567 -39.97529464   0.59661805].\n",
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      "Step : 1232 time: --> 0.16597461199760438 s, odometry: - [-43.844628   -39.41490404   0.6052191 ].\n",
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      "Step : 1250 time: --> 0.15351132301986217 s, odometry: - [-36.63895659 -34.08051917   0.66377841].\n",
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      "Step : 1260 time: --> 0.1496958100050688 s, odometry: - [-32.75728757 -30.93373646   0.69590866].\n",
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      "Step : 1276 time: --> 0.1385656429976225 s, odometry: - [-26.69969057 -25.71061885   0.73553987].\n",
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      "Step : 1281 time: --> 0.1356578210145235 s, odometry: - [-24.84793918 -24.03294678   0.7361962 ].\n",
      "Step : 1282 time: --> 0.13535769300162792 s, odometry: - [-24.47742515 -23.69720976   0.73602699].\n",
      "Step : 1283 time: --> 0.13466374701261521 s, odometry: - [-24.10732647 -23.36196313   0.74017545].\n",
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      "Step : 1285 time: --> 0.13349129001796245 s, odometry: - [-23.3687273  -22.68781839   0.7397764 ].\n",
      "Step : 1286 time: --> 0.13351571699976922 s, odometry: - [-22.99941764 -22.35075701   0.73970907].\n",
      "Step : 1287 time: --> 0.13285784800350667 s, odometry: - [-22.63008529 -22.01372049   0.74175248].\n",
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      "Step : 1291 time: --> 0.13193873798847197 s, odometry: - [-21.16125807 -20.65814755   0.74824337].\n",
      "Step : 1292 time: --> 0.13217925100028516 s, odometry: - [-20.79551216 -20.31861807   0.75207119].\n",
      "Step : 1293 time: --> 0.13050403599441052 s, odometry: - [-20.43037441 -19.97704169   0.74874852].\n",
      "Step : 1294 time: --> 0.13015236599743366 s, odometry: - [-20.06410373 -19.63668042   0.74813769].\n",
      "Step : 1295 time: --> 0.13076730999350547 s, odometry: - [-19.69762522 -19.29654294   0.75037202].\n",
      "Step : 1296 time: --> 0.1292018460035324 s, odometry: - [-19.3319076  -18.95558749   0.75240288].\n",
      "Step : 1297 time: --> 0.12839211700856687 s, odometry: - [-18.96688317 -18.61389001   0.74891864].\n",
      "Step : 1298 time: --> 0.1288260720074177 s, odometry: - [-18.6006704  -18.27346644   0.74903302].\n",
      "Step : 1299 time: --> 0.1283296070098877 s, odometry: - [-18.23480246 -17.93328539   0.7488445 ].\n",
      "Step : 1300 time: --> 0.12805382500588894 s, odometry: - [-17.86856446 -17.59288897   0.75565931].\n",
      "Step : 1301 time: --> 0.12591069899499416 s, odometry: - [-17.50465467 -17.25000464   0.75741429].\n",
      "Step : 1302 time: --> 0.12696142898499965 s, odometry: - [-17.14134721 -16.90648217   0.75774543].\n",
      "Step : 1303 time: --> 0.125510145008564 s, odometry: - [-16.77815351 -16.56283942   0.75925478].\n",
      "Step : 1304 time: --> 0.12589835299551486 s, odometry: - [-16.41547891 -16.21864887   0.764809  ].\n",
      "Step : 1305 time: --> 0.1247137719988823 s, odometry: - [-16.0547434  -15.87247019   0.76686069].\n",
      "Step : 1306 time: --> 0.1262000639885664 s, odometry: - [-15.69469714 -15.52553116   0.76754367].\n",
      "Step : 1307 time: --> 0.12394157500565052 s, odometry: - [-15.33488792 -15.1783463    0.77163922].\n",
      "Step : 1308 time: --> 0.12408353900909423 s, odometry: - [-14.97650363 -14.82969074   0.77391872].\n",
      "Step : 1309 time: --> 0.12228766000270844 s, odometry: - [-14.61891503 -14.48021915   0.77473692].\n",
      "Step : 1310 time: --> 0.12260930800437927 s, odometry: - [-14.26161248 -14.1304551    0.7757762 ].\n",
      "Step : 1311 time: --> 0.12211622799932957 s, odometry: - [-13.90467363 -13.7803199    0.77300714].\n",
      "Step : 1312 time: --> 0.12187656699120998 s, odometry: - [-13.5467666  -13.43117443   0.7746776 ].\n",
      "Step : 1313 time: --> 0.1202236839979887 s, odometry: - [-13.18944331 -13.08143158   0.7810665 ].\n",
      "Step : 1314 time: --> 0.12018722398579121 s, odometry: - [-12.83436177 -12.72941297   0.78386515].\n",
      "Step : 1315 time: --> 0.1199784519970417 s, odometry: - [-12.48026679 -12.376402     0.78441382].\n",
      "Step : 1316 time: --> 0.11926395699381828 s, odometry: - [-12.12636555 -12.0231968    0.78652262].\n",
      "Step : 1317 time: --> 0.11788247701525688 s, odometry: - [-11.77320994 -11.66924607   0.78305758].\n",
      "Step : 1318 time: --> 0.11855234499275684 s, odometry: - [-11.41883    -11.31652117   0.77827702].\n",
      "Step : 1319 time: --> 0.11698861300945282 s, odometry: - [-11.06276789 -10.96549443   0.77274938].\n",
      "Step : 1320 time: --> 0.11676276800036431 s, odometry: - [-10.70509757 -10.61675975   0.77295664].\n",
      "Step : 1321 time: --> 0.11547695298492909 s, odometry: - [-10.34843341 -10.26886187   0.77641929].\n",
      "Step : 1322 time: --> 0.11616426600515842 s, odometry: - [-9.99750752 -9.9241819   0.7771895 ].\n",
      "Step : 1323 time: --> 0.11550390501320362 s, odometry: - [-9.64988818 -9.5822232   0.77414202].\n",
      "Step : 1324 time: --> 0.11489000298082828 s, odometry: - [-9.30569506 -9.24569273  0.77003233].\n",
      "Step : 1325 time: --> 0.11381060498952865 s, odometry: - [-8.96313102 -8.91349774  0.77010283].\n",
      "Step : 1326 time: --> 0.11369836799800397 s, odometry: - [-8.62184394 -8.58249437  0.76634459].\n",
      "Step : 1327 time: --> 0.11290640099346638 s, odometry: - [-8.27973147 -8.25317659  0.76231362].\n",
      "Step : 1328 time: --> 0.1144866639971733 s, odometry: - [-7.94299105 -7.93163501  0.75795627].\n",
      "Step : 1329 time: --> 0.11258134600520134 s, odometry: - [-7.61094274 -7.61732837  0.75347913].\n",
      "Step : 1330 time: --> 0.11311791899800301 s, odometry: - [-7.28528914 -7.31182745  0.75063097].\n",
      "Step : 1331 time: --> 0.11156911699473858 s, odometry: - [-6.96360902 -7.01177204  0.74108652].\n",
      "Step : 1332 time: --> 0.11152568200230599 s, odometry: - [-6.63925069 -6.71495696  0.73666748].\n",
      "Step : 1333 time: --> 0.11051964600384236 s, odometry: - [-6.31876643 -6.42427867  0.72861576].\n",
      "Step : 1334 time: --> 0.111110504001379 s, odometry: - [-5.99490836 -6.13525874  0.72702936].\n",
      "Step : 1335 time: --> 0.11021240398287774 s, odometry: - [-5.673758   -5.84956918  0.7148178 ].\n",
      "Step : 1336 time: --> 0.10948576298356057 s, odometry: - [-5.35049203 -5.56899349  0.71279453].\n",
      "Step : 1337 time: --> 0.10922750601172447 s, odometry: - [-5.02855424 -5.29071062  0.71341023].\n",
      "Step : 1338 time: --> 0.10915394499897957 s, odometry: - [-4.70813301 -5.01339381  0.71334113].\n",
      "Step : 1339 time: --> 0.10767651000618934 s, odometry: - [-4.39351434 -4.741137    0.71825638].\n",
      "Step : 1340 time: --> 0.10833903598785401 s, odometry: - [-4.08544778 -4.4718906   0.72295708].\n",
      "Step : 1341 time: --> 0.10708494099974632 s, odometry: - [-3.77657286 -4.19936615  0.7331719 ].\n",
      "Step : 1342 time: --> 0.10795100900530816 s, odometry: - [-3.46681111 -3.92038046  0.74840242].\n",
      "Step : 1343 time: --> 0.1058463160097599 s, odometry: - [-3.15151215 -3.62758854  0.76274348].\n",
      "Step : 1344 time: --> 0.1053014770001173 s, odometry: - [-2.8204624  -3.31120862  0.76622853].\n",
      "Step : 1345 time: --> 0.10559048199653626 s, odometry: - [-2.48277084 -2.98622191  0.77343343].\n",
      "Step : 1346 time: --> 0.10588808400928974 s, odometry: - [-2.14988751 -2.66121049  0.79073709].\n",
      "Step : 1347 time: --> 0.10736693100631237 s, odometry: - [-1.81939999 -2.3271751   0.80510304].\n",
      "Step : 1348 time: --> 0.10401690199971199 s, odometry: - [-1.48740891 -1.98183558  0.82359994].\n",
      "Step : 1349 time: --> 0.10389882500469684 s, odometry: - [-1.15259398 -1.62041008  0.85093625].\n",
      "Step : 1350 time: --> 0.1027042139917612 s, odometry: - [-0.82295424 -1.24446108  0.88634627].\n",
      "Step : 1351 time: --> 0.10176959599554539 s, odometry: - [-0.50683073 -0.85707765  0.91724717].\n",
      "Step : 1352 time: --> 0.10145260499417783 s, odometry: - [-0.20282672 -0.46011221  0.94883983].\n",
      "Step : 1353 time: --> 0.10155263800919057 s, odometry: - [ 0.08592491 -0.05731543  0.97113418].\n",
      "End of sequence\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x900 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Imports\n",
    "import math\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scripts.diffdrive import DiffDriveVehicle\n",
    "from scripts.animation import Animator\n",
    "from scripts.mppi import MPPIControllerDiffDrive\n",
    "from scripts.utils import curr_time, debug_lock, plot_ref_vs_tracked_path, compute_erros, results_inputs\n",
    "\n",
    "# Setup simulation parameters\n",
    "# OBSTACLE_CIRCLES = np.array([+20.0,+20.0,1.0])\n",
    "# Obstacles are deifned in the global/inertial coordinate frame\n",
    "\n",
    "TRACK_TYPE = \"figure_eight\" # \"oval\", \"figure_eight\"\n",
    "show_animation = False # Default true\n",
    "save_animation = False # Default False\n",
    "delta_t = 0.1 # [sec]\n",
    "sim_steps = 10000 # [steps]\n",
    "num_samples = 100 # [int]\n",
    "horizon_ = 20 # [int]\n",
    "print(f\"[INFO] delta_t : {delta_t:.2f}[s] , sim_steps : {sim_steps}[steps], total_sim_time : {delta_t*sim_steps:.2f}[s]\")\n",
    "actual_steps = 0\n",
    "\n",
    "# Load and visualize reference path\n",
    "if (TRACK_TYPE == \"oval_path\"):\n",
    "    ref_path = np.genfromtxt('./data/ovalpath_diff.csv', delimiter=',', skip_header=1)\n",
    "    \n",
    "    OBSTACLE_CIRCLES = np.array([\n",
    "    [+ 10.0, +5.0, 4.0], # pos_x, pos_y, radius [m] in the global frame\n",
    "    [+10.0, 33.0, 2.0], \n",
    "    ])\n",
    "\n",
    "elif (TRACK_TYPE == \"figure_eight\"):\n",
    "    ref_path = np.genfromtxt('./data/figure_eight.csv', delimiter=',', skip_header=1)\n",
    "\n",
    "    OBSTACLE_CIRCLES = np.array([\n",
    "    [+ 25.0, +30.0, 1.0], # pos_x, pos_y, radius [m] in the global frame\n",
    "    [+25.0, 32.0, 1.0], \n",
    "    ])\n",
    "\n",
    "else:\n",
    "    raise ValueError(f\"Requested path not available\")\n",
    "\n",
    "# Define vehicle type and MPPI\n",
    "init_state = np.array([0, 0, 0.0]) # [x,y,theta]\n",
    "vehicle = DiffDriveVehicle(delta_t=delta_t,\n",
    "                           ref_path=ref_path[:, 0:2], # np.ndarray([])\n",
    "                           abs_vb_val= 5.0, #[m/s]\n",
    "                           abs_omega_val=1.5, # [rad/s]\n",
    "                           obstacle_circles = OBSTACLE_CIRCLES,\n",
    "                           init_state=init_state)\n",
    "\n",
    "animator = Animator(vehicle_model=vehicle)\n",
    "if TRACK_TYPE == \"oval_path\":\n",
    "    aa = 80 # x,y weight\n",
    "    bb = 1 # yaw weight\n",
    "    cc = 80 # velocity weight\n",
    "else:\n",
    "    aa = 100.0 # x,y weight\n",
    "    bb = 20.0 # yaw weight\n",
    "    cc = 60.0 # velocity weight\n",
    "\n",
    "dd1 = 0.01\n",
    "dd2 = 0.01\n",
    "cost_arr = np.array([aa, aa, bb, cc])\n",
    "sigma_arr = np.array([[dd1, 0.0], [0.0, dd2]])\n",
    "\n",
    "# Define MPPI object\n",
    "# initialize a mppi controller for the vehicle\n",
    "mppi = MPPIControllerDiffDrive(\n",
    "    vehicle_model = vehicle,\n",
    "    delta_t = delta_t*2.0, # [s]\n",
    "    abs_vb_val = vehicle.abs_vb_val, # [m/s]\n",
    "    abs_omega_val = vehicle.abs_omega_val, # [rad/s]\n",
    "    ref_path = ref_path, # ndarray, size is <num_of_waypoints x 2>\n",
    "    horizon_step_T = horizon_, # [steps]\n",
    "    number_of_samples_K = num_samples, # [samples]\n",
    "    param_exploration = 0.05,\n",
    "    param_lambda = 50, # larger value of lambda heavily weighs low-cost path\n",
    "    param_alpha = 0.98,\n",
    "    sigma_matrix = sigma_arr,\n",
    "    stage_cost_weight = cost_arr, # weight for [x, y, yaw, v]\n",
    "    terminal_cost_weight = cost_arr, # weight for [x, y, yaw, v]\n",
    "    obstacle_circles = OBSTACLE_CIRCLES, # [obs_x, obs_y, obs_radius]\n",
    "    collision_safety_margin_rate = 1.2, # safety margin for collision check\n",
    ")\n",
    "\n",
    "# simulation loop\n",
    "warm_up_step = -1\n",
    "time_per_step = []\n",
    "done_flag = False\n",
    "tracked_path = [] # Odometry of robot\n",
    "# Main loop\n",
    "for i in range(sim_steps):\n",
    "    # get current state of vehicle\n",
    "    current_state = vehicle.get_state() # [x,y,yaw]\n",
    "    tt = curr_time()\n",
    "    # calculate input force with MPPI\n",
    "    optim_u, optim_u_seq, optimal_traj, sampled_traj_list, done_flag = mppi.calc_control_input(observed_x = current_state)\n",
    "    if (done_flag == False):\n",
    "        tt2 = curr_time()\n",
    "        tt_s = (tt2 - tt)/1000\n",
    "        time_per_step.append(tt_s)\n",
    "        # Give an initial velocity\n",
    "        if i<=warm_up_step:\n",
    "            optim_u = [1.0,0]\n",
    "        vehicle.update(u=optim_u, x_t_prev= current_state, delta_t=delta_t, \n",
    "                    optimal_traj=optimal_traj[:, 0:2], \n",
    "                    sampled_traj_list=sampled_traj_list[:, :, 0:2])\n",
    "        tracked_path.append(vehicle.state.copy())\n",
    "        if show_animation:\n",
    "            animator.draw_frame(vehicle.out_arr)\n",
    "        print(f\"Step : {i} time: --> {tt_s} s, odometry: - {vehicle.state.copy()}.\")\n",
    "        actual_steps+=1\n",
    "    else:\n",
    "        print(f\"End of sequence\")\n",
    "        break\n",
    "if show_animation:\n",
    "    animator.show_animation(interval_ms=delta_t*1000) # show animation\n",
    "if save_animation:\n",
    "    animator.save_animation(\"result.mp4\", interval=int(delta_t * 1000), movie_writer=\"ffmpeg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE for X-position: 0.3240930716543267 m\n",
      "RMSE for Y-position: 0.39416794096318386 m\n",
      "RMSE for Yaw : 5.3834676936665184 degree\n",
      "Mean linear velocity: 4.501264343641467 m/s\n",
      "Mean angular velocity: 0.007172335126171517 rad/s\n",
      "Actual number of steps: 1354 and total simulation time: 135.40 seconds\n",
      "Average time per step: 0.234 ms\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Reference path vs Tracked path\n",
    "matched_path, matched_indicies = plot_ref_vs_tracked_path(ref_path=ref_path,\n",
    "                                        tracked_path=tracked_path, \n",
    "                                        obstacle_arr=OBSTACLE_CIRCLES,\n",
    "                                        save_plot=True)\n",
    "\n",
    "# Compute RMSE errors\n",
    "compute_erros(ref_path=ref_path, matched_path=matched_path)\n",
    "\n",
    "# Average linear and angular velocities and their plots\n",
    "results_inputs(u_optims=vehicle.u_history, matched_indices=matched_indicies, step_val=actual_steps)\n",
    "\n",
    "# Computation steps\n",
    "print(f\"Actual number of steps: {actual_steps} and total simulation time: {actual_steps*delta_t:.2f} seconds\")\n",
    "print(f\"Average time per step: {np.mean(time_per_step):0.3f} ms\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ee7500_proj",
   "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": "3.12.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}