SLAM-Course - 01 - Introduction to Robot Mapping (2013/14; Cyrill Stachniss)

Поділитися
Вставка
  • Опубліковано 2 жов 2024

КОМЕНТАРІ • 105

  • @jak0bw651
    @jak0bw651 3 роки тому +7

    this feels like a mix of a well researched and produced tutorial and my actualy lectures at university :D love it

  • @CyrillStachniss
    @CyrillStachniss  11 років тому +117

    You are welcome - great to hear that the course helps understanding the material!

    • @obedulla1
      @obedulla1 7 років тому

      good explanation. well organized topics.

    • @PitoSalas
      @PitoSalas 5 років тому +2

      Great course. Would you be willing to share the slides with me? You have some nice illustrations

    • @owardocarther30
      @owardocarther30 3 роки тому

      It is still helping people ! Such a great thank you !!!

    • @utkarshranjan7903
      @utkarshranjan7903 3 роки тому

      Can you add slides in the description, Would be very helpfull

  • @omarlugos
    @omarlugos 10 місяців тому +1

    i took this course to finish my mater thesis about slam, i was using a kinect camera to map my university.

  • @janzaibmbaloch5484
    @janzaibmbaloch5484 7 років тому +23

    This is exactly what I was looking for. Thank you Universitat Frieburg.

  • @RESC_Eng
    @RESC_Eng 3 роки тому

    Thank you so much this is an amazing course and it is rarely to find an excellent demonstration about that topic

  • @hhj989
    @hhj989 8 років тому +57

    I have never seen such a wonderful course!

    • @CyrillStachniss
      @CyrillStachniss  7 років тому +1

      Thanks

    • @nicolasperez4292
      @nicolasperez4292 3 роки тому +2

      @@CyrillStachniss thank you so much for making these lectures available to everyone :) you are doing a great service to the scientific and engineering community :)

  • @GCOMRacquet
    @GCOMRacquet 11 років тому

    Yeah they really do! I'll going to watch all of your Courses, hope it's ok to ask if there are any questions about the material :)

  • @sylvesterfowzan5417
    @sylvesterfowzan5417 6 років тому +1

    Sir
    i have a doubt? in this tutorial you explained us how slam works and mapping but you given everything as LA derivations i have doubt here that how to convert these derivations in to real-time coding in python or in C++ to make practically possible,because i'm still learning and exploring...

  • @josejimenez850
    @josejimenez850 Рік тому +2

    Thank you sir!! Please continue to spread knowledge on your platform

  • @kashifnoori6834
    @kashifnoori6834 7 років тому +1

    I am in 2nd Year of B.Tech course ! Can you suggest prior Mathematical knowledge for completing this course or list of prerequisites . I need to learn SLAM for an upcoming project on Autonomous Quadcopter !

  • @CyrillStachniss
    @CyrillStachniss  11 років тому +3

    No, the environment itself does not change so there is no time dependency as for the x, z, or u.

  • @jont7207
    @jont7207 7 років тому +2

    That mint is scary. what if it sends out mappings of your house to dubious people. now they know your house inside and out. it would be a serious IoT issue.
    nice course btw. Thank you!

  • @tjdwnd9529
    @tjdwnd9529 4 роки тому

    14:58 hmm but there is no landmark...🤔 that was so fun and nice expression for measurement update 😂😂 thank you for these awesome lectures!

  • @AliRaza786
    @AliRaza786 8 років тому +12

    you are a life saver :) perfectly explained, thank you so much for recording this video, i was thinking there will be no lecture on SLAM but fortunately i found it. Thankyou again.

    • @kashifnoori6834
      @kashifnoori6834 7 років тому +2

      Feeling the same ! :) I am interested to know where you applied it , i am going to use it on making Autonomous QuadCopter but in my area there is no one who can hlp with it ! Any suggestions regarding how should i start ! Thanx

  • @philipakomolafe
    @philipakomolafe 10 місяців тому

    Okay, Sir Cyril what if you don't want wire linings as demarcation. Can the SLAM method still be durable.
    Or what other methods of mapping and localization helps a lawn mower possibly mower an area effectively.

    • @CyrillStachniss
      @CyrillStachniss  10 місяців тому +1

      You will likely need some sensing of the environment or some form of beacon placed in the garden that you can sense

  • @zwatcs
    @zwatcs 10 років тому +4

    Thanks, awesome introduction. My professor tends to skip the basics!

  • @madushaperera8115
    @madushaperera8115 6 років тому +2

    Simply wow. Thank you very much for sharing.
    (from the other part of the world : Sri Lanka)

  • @01nm
    @01nm 7 років тому +1

    Okay... Where's your Patreon page at? My Mobile Robotics lecturer at Warwick could learn a thing or two from your lecture quality.

    • @CyrillStachniss
      @CyrillStachniss  7 років тому

      No Patreon (yet) - but may be I should think about that...

  • @blenderNOOb69
    @blenderNOOb69 Рік тому

    If the landmarks are very distinctive, why not triangle between those and the vehicle. As they did 500 years ago.

    • @CyrillStachniss
      @CyrillStachniss  Рік тому

      In the old days, people were going to the landmarks (towers) and take measurements there towards other towers. This created these networks. The problem on the robot is a different one.

  • @jayaramjonnada5855
    @jayaramjonnada5855 Рік тому

    At 18:00, shouldn't the grey star be below the gold star(the star below the word same). Because in its wrong path the distance of the star from the robot measured by the robot is less than the actual distance so, in estimation of the star's position from the robot's path(the real one through which it should go) should be less. so, it should be nearer.

  • @jeova0sanctus0unus
    @jeova0sanctus0unus 5 років тому +2

    This is quite helpfull, you have my thanks.

  • @CyrillStachniss
    @CyrillStachniss  11 років тому +1

    As soon as the questions are focused and precisely formulated, no problem.

  • @michelangeligayonperez5494
    @michelangeligayonperez5494 7 років тому +1

    Hi Mr. Stachniss! Thanks for this video-lectures! I am new in this area (SLAM). I am trying to implement SLAM in a car robot with a four ultrasonic and a stereo camera. I having difficulties choosing and adapting one of the slam algorithms to this particular case. Could you give some advice about it?

    • @hanenabdelmoula4147
      @hanenabdelmoula4147 5 років тому

      the same situation please if you can help me with anything about , hanen.abdelmoula.enetcom @gmail.com

  • @PappaRasu
    @PappaRasu 3 роки тому

    Nice lessons Sir. Great work

  • @adriennewinter9949
    @adriennewinter9949 2 роки тому +1

    Thank you Cyrill for these uploads! I am a Masters student doing a dissertation only project and your videos are saving me so much time and confusion! Really great.

  • @welidbenchouche
    @welidbenchouche 4 роки тому

    this is actually amazing, i have a question though, if i were to use model predictive control to minimize navigation errors, how could i approach that ? and how about fault tolerant control, do you have any example of applying it for navigation ? my system is a differential drive, thank you in advance

  • @aamirbadershah887
    @aamirbadershah887 3 роки тому +1

    Are we just going to ignore the fact that this guy has undergone great fat loss transformation now and looks ripped AF in 2021

  • @youssefhany4846
    @youssefhany4846 Рік тому

    Thank you very much for spreading knowledge ❤️ Are the slides of these course available to recall them from time to time?

  • @mfraifer
    @mfraifer 2 роки тому +1

    it was great lecture.

  • @shreyansh2847
    @shreyansh2847 6 років тому

    Where can I find these slides? It will be really great if you could add it's link in the description

  • @studymaterial7254
    @studymaterial7254 4 роки тому

    Thank you, sir, for these lectures. I'm doing a project on SLAM, and I have some questions about slam. can you please help me out to solve those problems?
    (Lots of love from INDIA)

  • @pannagasudarshan6639
    @pannagasudarshan6639 Рік тому +1

    Beautifully done!

  • @arvindkumarvishwakarma1428
    @arvindkumarvishwakarma1428 4 роки тому

    SLAM words of full form
    Releted with safety.

  • @ruanjiayang
    @ruanjiayang 5 років тому

    Could you please tell if we can get a copy of these nice slides somewhere?

  • @shrijank522
    @shrijank522 6 років тому

    Perfectly Explained.
    So i was currently working with dynamic SLAM problem. Could you suggest which sensors can be more effective in dense dynamic environment?

  • @Vish-i7c
    @Vish-i7c Місяць тому

    Are course homework/lab available besides slides?

  • @vaibhavkumarpathak3808
    @vaibhavkumarpathak3808 4 роки тому

    A well explained SLAM lecture. Thank you teach.

  • @pedropgusmao
    @pedropgusmao 9 років тому

    Excellent video. Now, when I was studying SLAM using Probabilistic Robotics I was a bit taken aback about the fact that odometry was actually perceived as control. But when one looks close at it, odometry is only reporting what the robot thinks it has done, which is basically what you told it to do (control). It basically just translates your commands into some calculation supposing that internal parameter (such as wheel diameter) are correct.

  • @solutions-ai
    @solutions-ai Рік тому

    Thanks Sir.

  • @GCOMRacquet
    @GCOMRacquet 11 років тому

    ok, im fine with that. Just thought that since m represent the map we obtain from the measurements, it change or let me say its getting bigger for every timestep we do. So that z(t) depends on a other map then then z(t-5) and so on.
    But i guess the map we obtained at (t-1) looks different then at (t) but its still the same map/environment we working with.
    Thanks for the Help.

  • @rohitgawas2492
    @rohitgawas2492 5 років тому

    I found it very useful and thanks a lot for posting lectures on SLAM and explaining it in so detail.

  • @shoumikghosal
    @shoumikghosal 8 років тому +1

    Thank you so much for the uploads. Feels so good to be getting my attention span back while watching your lectures! Hope I keep coming across and learning from amazing minds like you.

  • @SubodhMishrasubEE
    @SubodhMishrasubEE 6 років тому

    I hope that the people who have disliked this video get a place in heaven :p

  • @MuhammadSaad-sp8ui
    @MuhammadSaad-sp8ui 7 місяців тому

    Can you please share course materials?

  • @oldcowbb
    @oldcowbb 4 роки тому

    come on and slam, and welcome to the jam

  • @doukhioualid4804
    @doukhioualid4804 8 років тому +1

    thank you very much , this is what im looking forrrrrr

  • @dungKHTNcs
    @dungKHTNcs 8 років тому

    Thanks so much. It's very informative and easy to approach SLAM :)

  • @cIynamen
    @cIynamen 10 років тому

    I just watched the ekf and ukf videos, they were great. Now I'm going to watch the entire course. Thanks a lot for making the video available!

  • @pelodetiffer8741
    @pelodetiffer8741 7 років тому +1

    This what i want!

  • @江左林殊
    @江左林殊 7 років тому

    Dear professor Cyrill Stachniss, I am an undergraduate student of China. I am writing to ask would you please offer me some information about where can I buy the book you use in this course? I am really interested in SLAM. Thank you.

    • @fangjunkuang5061
      @fangjunkuang5061 7 років тому

      江左林殊 课程主页有链接

    • @CyrillStachniss
      @CyrillStachniss  7 років тому +1

      The Probabilistic Robotics Course should be a rather good starting point on the basics. From there, I would continue with tutorials and by implementing papers.

    • @江左林殊
      @江左林殊 7 років тому

      Thank you!

  • @OscarPanczenko
    @OscarPanczenko 4 роки тому

    Brilliant

  • @waqasaps
    @waqasaps 3 роки тому

    state estimation vs localization?

  • @hamidmajidi5103
    @hamidmajidi5103 5 років тому

    You are great tutor. Thank you for sharing your knowledge with everyone without any expectations.

  • @ThanhNguyen-os2wi
    @ThanhNguyen-os2wi 4 роки тому

    51:58 Việt Nam điểm danh :3

  • @Tranksmighty
    @Tranksmighty 4 роки тому

    wish you taught at my uni....

  • @bassmamedhat7171
    @bassmamedhat7171 2 роки тому

    is there a way to get the slides?

  • @高超-y6o
    @高超-y6o 8 років тому

    A nice source to learn SLAM.

  • @MOHAMMADALAHDAB
    @MOHAMMADALAHDAB 8 років тому

    thank you so much for the uploads !
    this is really great !
    thank you :D

  • @GCOMRacquet
    @GCOMRacquet 11 років тому

    Thanks for this uploads. They are a big help for me to get into the basics of SLAM. I have read most of your papers but with this videos, explain step by step, its much easier to get it. Thank you very much.

  • @刘盼盼-g8h
    @刘盼盼-g8h 8 років тому

    that's exactly what i need! how to download it?

  • @刘盼盼-g8h
    @刘盼盼-g8h 8 років тому

    it would be better with subtitle

  • @youryella
    @youryella 4 роки тому

    1:15:00 - Summary

  • @romniyepez5206
    @romniyepez5206 6 років тому

    32:11 Definition of SLAM Process

  • @cliffanthony1
    @cliffanthony1 5 років тому

    Nice one Cyrill

  • @櫻田繁
    @櫻田繁 4 роки тому

    b

  • @loc_research
    @loc_research 4 роки тому

    Thanks!

  • @allanantony8423
    @allanantony8423 5 років тому

    This is amazing =) Great Job

  • @HassanOmariprofile
    @HassanOmariprofile 5 років тому

    this is just awesome

  • @minhdaotran6907
    @minhdaotran6907 6 років тому

    thanks you so much .

  • @paullee2593
    @paullee2593 6 років тому

    Great explanation! Thanks!

  • @jurgenlange5043
    @jurgenlange5043 8 років тому

    Thanks for this uploads.

  • @GaryPaluk
    @GaryPaluk 7 років тому

    Excellent primer!

  • @sandrojua9232
    @sandrojua9232 5 років тому

    Estate Estimation 00:03:10

  • @tawandadenzel6636
    @tawandadenzel6636 8 років тому

    cool uploads.

  • @hadrianguangxianhe1449
    @hadrianguangxianhe1449 7 років тому

    Thank you

  • @Bjorntenbroeke03
    @Bjorntenbroeke03 8 років тому

    Nice!

  • @chanchoi5076
    @chanchoi5076 7 років тому

    thank you for sharing

  • @fangjunkuang5061
    @fangjunkuang5061 7 років тому

    Danke

  • @GCOMRacquet
    @GCOMRacquet 11 років тому

    Do we allways just have one map? Should not on the Graphical Model for every timestep a map. Just like the observations z(t-1), z(t)...z(T) there is a map m(t-1), m(t)...m(T)?

  • @the_guy_with_pajamas
    @the_guy_with_pajamas 5 років тому

    Excellent course and equally understandable teaching. Thank you very much!

  • @fuckugplus
    @fuckugplus Рік тому

    It know where is its because it know where it isnt