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Hummingbird
Germany
เข้าร่วมเมื่อ 20 ก.พ. 2015
Life in Robotics and Technology.
Experimenting with career and life, a little too much
Experimenting with career and life, a little too much
Visual Odometry Vs Visual SLAM
This video talks about the conceptual differences between Visual Odometry and Visual SLAM
มุมมอง: 318
วีดีโอ
YOLO11/YOLO10 and DeepSORT: Object Detection and Tracking (Concept and Python Code)
มุมมอง 1.2K3 หลายเดือนก่อน
Ultralytics YOLO11/YOLO10 and DeepSORT based Object Detection and Tracking with concept and full python code Code on github: github.com/thehummingbird/computer_vision Yolo11 pytorch models: docs.ultralytics.com/models/yolo11/#performance-metrics Yolo10 pytorch models: docs.ultralytics.com/models/yolov10/#performance
What is Pytorch, TF, TFLite, TensorRT, ONNX?
มุมมอง 4603 หลายเดือนก่อน
Basic ideas behind Pytorch, TF, TFLite, TensorRT, ONNX in machine learning
Visual Odometry Series - Part 2 (C++ Code for Monocular Visual Odometry)
มุมมอง 6784 หลายเดือนก่อน
We build a monocular visual odometry feature in C for the KITTI dataset Code on github - github.com/thehummingbird/robotics_demos/tree/main/monocular_vo KITTI Dataset - www.cvlibs.net/datasets/kitti/eval_odometry.php
Visual Odometry Series - Part 1 (Concept and Math)
มุมมอง 1.1K6 หลายเดือนก่อน
This is part 1 of this Visual Odometry series. It covers the concept and the mathematics behind Monocular Visual Odometry. The next part implements it in C Link to tutorial papers from Scaramuzza and Fraundorfer: rpg.ifi.uzh.ch/visual_odometry_tutorial.html
Asynchronous Vs Multithreading Vs Multiprocessing (Concept and Code)
มุมมอง 4908 หลายเดือนก่อน
This video explains is what asynchronous programming, multithreading and multiprocessing followed by Python implementation for each
Hands-On Py Trees - Part 1 (Action, Condition, Sequence, Decorator)
มุมมอง 3Kปีที่แล้ว
Part 1 of Hands-On Py trees series where we introduce Action, Condition, Sequence,Decorator through an example. Code: github.com/thehummingbird/robotics_demos/tree/main/py_trees
Understanding Precision and Recall in Computer Vision (Example Based)
มุมมอง 239ปีที่แล้ว
This is an example based understanding of Precision and Recall in Computer Vision
Unfiltered Conversation - took a break, some challenges, next videos
มุมมอง 170ปีที่แล้ว
Unfiltered Conversation - took a break, some challenges, next videos
Kalman Filter Series - Part 5 (Python 1D Kalman Filter from scratch)
มุมมอง 2.3Kปีที่แล้ว
This is Part 5 of the Kalman Filter Series where we build a 1D Kalman FIlter from scratch in Python. It has been made in collaboration with Mathias Mantelli. Here are our LinkedIn and Twitter handles: Github link: github.com/thehummingbird/robotics_demos/blob/main/kalman_filter/1D/kf.py Mathias Mantelli: www.linkedin.com/in/mathiasma... MathiasMantelli Sharad Maheshwari: www.linkedi...
Kalman Filter Series - Part 4 (Formal Equations)
มุมมอง 933ปีที่แล้ว
This is Part 4 of the Kalman Filter Series where we finally derive and see the Kalam Filter based on everything we've learnt in the series. It has been made in collaboration with Mathias Mantelli. Here are our LinkedIn and Twitter handles: Mathias Mantelli: www.linkedin.com/in/mathiasmantelli/ MathiasMantelli Sharad Maheshwari: www.linkedin.com/in/sharad-maheshwari-b85626ba/ twitter...
Kalman Filter Series - Part 3 (Bayes Filter)
มุมมอง 1.2Kปีที่แล้ว
This is Part 3 of the Kalman Filter Series where we understand what a Bayes Filter is with an example based derivation Blog version of this video: medium.com/p/f2fa9c0b5c95 It has been made in collaboration with Mathias Mantelli. Here are our LinkedIn and Twitter handles: Mathias Mantelli: www.linkedin.com/in/mathiasma... MathiasMantelli Sharad Maheshwari: www.linkedin.com/in/sharad...
Kalman Filter Series - Part 2 (Alpha Beta Filter)
มุมมอง 2.3Kปีที่แล้ว
This is Part 2 of the Kalman Filter Series where we understand what an Alpha Beta Filter is using an example. Blog version of this video: medium.com/p/6d2e2b28d4cf It has been made in collaboration with Mathias Mantelli. Here are our LinkedIn and Twitter handles: Mathias Mantelli: www.linkedin.com/in/mathiasma... MathiasMantelli Sharad Maheshwari: www.linkedin.com/in/sharad-ma... tw...
Unfiltered Conversation - What's important in a tech career? It's not just tech skills
มุมมอง 258ปีที่แล้ว
Unfiltered Conversation - What's important in a tech career? It's not just tech skills
Kalman Filter Series - Part 1 (Intuitive Understanding)
มุมมอง 2.3Kปีที่แล้ว
Kalman Filter Series - Part 1 (Intuitive Understanding)
Channel Update: more robotics, gear upgrade
มุมมอง 239ปีที่แล้ว
Channel Update: more robotics, gear upgrade
Unfiltered Conversation - My work as a Robotics Engineer
มุมมอง 1.3Kปีที่แล้ว
Unfiltered Conversation - My work as a Robotics Engineer
ROS 2 Navigation - Part 4.2 ( Nav2 Project - build a Patrolling Robot)
มุมมอง 6Kปีที่แล้ว
ROS 2 Navigation - Part 4.2 ( Nav2 Project - build a Patrolling Robot)
ROS 2 Navigation - Part 4.1 ( Nav2 Project - build a Patrolling Robot)
มุมมอง 5Kปีที่แล้ว
ROS 2 Navigation - Part 4.1 ( Nav2 Project - build a Patrolling Robot)
ROS 2 Navigation - Part 3 (creating Nav2 Simple demo with TurtleBot3)
มุมมอง 11Kปีที่แล้ว
ROS 2 Navigation - Part 3 (creating Nav2 Simple demo with TurtleBot3)
ROS 2 Navigation - Part 2 (ROS 1 Vs ROS 2 Nav Design in detail)
มุมมอง 5Kปีที่แล้ว
ROS 2 Navigation - Part 2 (ROS 1 Vs ROS 2 Nav Design in detail)
ROS 2 Navigation - Part 1 (Basic Navigation Concepts)
มุมมอง 5Kปีที่แล้ว
ROS 2 Navigation - Part 1 (Basic Navigation Concepts)
Unfiltered Conversation - My experiences with Startups Vs Academia Vs MNCs
มุมมอง 330ปีที่แล้ว
Unfiltered Conversation - My experiences with Startups Vs Academia Vs MNCs
Unfiltered Conversation - My detailed journey into Robotics
มุมมอง 546ปีที่แล้ว
Unfiltered Conversation - My detailed journey into Robotics
ROS 2 - spin, spin_once, spin_until_future_complete
มุมมอง 2.8K2 ปีที่แล้ว
ROS 2 - spin, spin_once, spin_until_future_complete
Hands-On ROS2 - Part 5 (Unit/Integration Tests)
มุมมอง 5K2 ปีที่แล้ว
Hands-On ROS2 - Part 5 (Unit/Integration Tests)
how to choose and estimate the values of alpha and beta in real scenario?
What if you have a pen, pineapple, apple, pen?
Will this be helpful for three wheeler detection?
Yeah. Depends on the orientation of the vehicle (if it’s clear that there’s a three wheeler). But in general, it can
Can you please tell me why does it keep on repeating from location 1,2,3,4 and go backto one again, i’m very comfused😢
So the packages that we make in the terminal are what will correspond in your example of brain, actuator and perceptor? How do I understand what a node is? What is a module? What exactly does ros does?
Nice
apreciate it!!
Very insightful! 👍👍
clear and good explanation.
Thank you! I watched few of your videos and you are really good at explaining things. I will definitely watch more on this topic
Nice video. I was looking for Part 2 but can't find it. Did you make a part 2?
Thank you very much for your sharing, it was greate.
Bro, you're great! Thanks for all the ROS videos. Much appreciated!
Does ROS2 Humble support python 3.11 version?
Is vslam really good compared to lidar based slam ? It seems that it does not guarantee localization that is when lost it cannot localize again. Btw nice video as always 😉
Great Channel!!
Wow Gazebo graphics are really ridiculous. But different than Webots it at least works.
Hi, Can you please share groot2 and it's working.
at 4:12 , there is an error on formulas, R is the measurement noise covariance which should be in the kalman gain, and Q is process noise covariance which should be in the prediction . replace Q and R in the formulas please.
Some books/resources use Q for measurement noise and R for process noise, while some do the opposite. We follow the former. You can decide which convention to choose.
Thank you for this video 😊😊😊
This is probably the best video on this topic. Straight to the point, still very in-depth, good code, no nonsense, professional and clear, easy for anyone to follow, and the code can be modified to create your own, if you have anything different or new to add/experiment with! For many reasons, this video is VERY well done. 🔥
Glad to be of help :)
I have watched all 4 videos up to this point and you have done an excellent job of teaching the Kalman filter. It's a shame these videos are not getting more views - they deserve more attention. Well done.
Glad to be of help :)
I'm using ros2-jazzy. The turtlebot3 git doesn't have any jazzy branches. Should I just use ros2-devel?
I tried ros2-devel and got many errors.
@@TheHG20 I faced similar issues, I guess ROS2 needs a few more years to become as mature as ROS1.
@@patham9 I switched to this: www.youtube.com/@ArticulatedRobotics/videos
ROS2 is a mess, but I can share a working VM if you are interested.
@@patham9 Not necessary. There are other more up-to-date TH-cam courses on ROS2, Gazebo, and sensors like Lidar.
how can i use tb3 on custom maps and perform the same patrolling operation
You need to generate and save your custom map using slam toolbox and then use the map (instead of the one here) while navigating
Great video. Thank you. Keep up the good work.
how to contact with you any source of point to make ???
sharadmaheshwari19@gmail.com
Thanks bro! I implemented your code on cLion. It really helped me to understand visual odometry properly.
absolute crystal clear explanation !!! Loved it
just when i was about to give up on nav2
But what if im working on only software part of the robot and not the hardware
Heavily subjective. If you need to test on real robots, in person might be better. If not (like open source for packages), fully remote might be okay
good, any help on visual odometry in ros2 c++
@@rajmeetsingh1625 haven’t scheduled a video for that yet
Amazing , some one was asking about detailed VO and here now we have one . Keep up the good work
Haha thanks Luqman! You too. Great work
Thank you!
you are a lifesaver
Well done! 👏
Great explanation!!, Thanks for this tutorial, Please keep posting such tutorials
what does it mean??
Hello, your work is remartkable but can i ask a question? I am now trying to build a project based on turtlesim, but i cant find any way to implement this logic with publishers and subcribers. What i trynna do is: first get the pose of turtle, then calcute velocity to send to the turtle, when the turtle have done executed that velocity command then i want to check the pose again, all that step in one spin. Does i need to do something else, it is related to future variable? Thanks
Very nice explanation. I was trying to find an overview of behavior trees for robotics and this is by far the best I’ve found.
May i know your Instagram ??
This video is so much underrated... You did a great job to explain the idea and principles behind ROS that I haven't found so far. Thanks a lot!!!
nice explanation , waiting for the next parts soon.
You are a God send!! Literally. keep it up! You are very talented in teaching and explaining. 🙂
For a waypoint navigation autonomous vehicle in a gps denied environments how can i move the vehicle from onepoint to other point using imu data?As i know only starting and ending waypoints.
what is the difference between asynchronous and multiprocessing? since they are both parallel?
This is a great video. It and your video about Py Trees gave me a much better understanding of both the theory and practice of behavior trees. That said, after doing some more research, I think this video needs a caveat that behavior trees aren't strictly better than FSMs. The speaker at 19:26 of "AI Arborist: Proper Cultivation and Care for Your Behavior Trees" makes a good case that, broadly speaking, AIs should use FSMs to decide _what_ to do, and then use BTs to decide _how_ to do it.
can you please make a tutorial on the Action communication type in ROS? I have been loving your content up until now... very insightful and helpful.. Thanks!
after i run the command ros2 launch ros_test_py talker_listener.launch.py, it blocks, no msg output,only i enter cirl+c,the talker_node and the listener_node will print one message respectivly
hello do you have any idea about the role of the debug vector in the offboard control mode
I unfortunately haven’t worked on that yet
Awesome explanation. Thanks a lot 🙏