Robotics with Sakshay
Robotics with Sakshay
  • Видео 78
  • Просмотров 134 145
DDPG | Panda Robot Arm | Deep Reinforcement Learning
DDPG (Deep Deterministic Policy Gradient) is a reinforcement learning technique for continuous action spaces that combines Deep Q Learning and Policy Gradients. DDPG is an Actor Critic based algorithm, where the Actor learns the optimal policy to determine the next action in a state and the Critic acts a Q-value network to score the actions generated by the Actor. In this video, we apply the DDPG algorithm to the Robot Reacher task using the Panda Robot Arm.
Feel free to leave a comment or message me on Twitter/LinkedIn in case of any questions, doubts, suggestions or improvements.
Twitter: MahnaSakshay
LinkedIn: www.linkedin.com/in/sakshaymahna/
Links
Notebook Code: www.kaggle.com...
Просмотров: 4 049

Видео

Unboxing the TortoiseBot Robot from RigBetel Labs
Просмотров 1,4 тыс.2 года назад
In this video, we are going to unbox and assemble the TortoiseBot Robot from RigBetel Labs. TortoiseBot is a minimalistic mobile robot that runs on ROS - Robot Operating System. The complete robot is Open Source. It can do typical Mobile Robot tasks like Mapping, Localization and Navigation. Buy TortoiseBot Here: rigbetellabs.com/shop Feel free to leave a comment or message me on Twitter/Linked...
Car Following | OpenCV Object Tracker | Machine Learning in ROS
Просмотров 2 тыс.2 года назад
Object Tracking is the task of locating and keeping track of a moving object in a video. OpenCV provides us with a number of built-in functions to do Object Tracking. In this video, we program an application for a Self Driving Car in ROS (Robot Operating System) to follow the car, driving in front of it using Object Tracking techniques. Feel free to leave a comment or message me on Twitter/Link...
DQN | Self Driving Car on Highway | Deep Reinforcement Learning
Просмотров 2 тыс.2 года назад
Q Learning is one of the most popular Reinforcement Learning algorithm. Q Learning works by learning the Q - Value function for a given environment and using that to derive the optimal policy. Deep Q Learning makes use of Deep Neural Networks to estimate the Q Value function in the classical Q Learning technique. In this video, we apply the Deep Q Learning technique to teach a Self Driving Car ...
Obstacle Avoidance | Neural Networks | Machine Learning in ROS
Просмотров 6 тыс.2 года назад
Neural Networks are a Supervised Learning based Machine Learning technique. In this video, we program the Data Collection Pipeline and train the Neural Network model to avoid obstacles in the environment. The TurtleBot3 robot is used for this task in a ROS (Robot Operating System) based simulation. Feel free to leave a comment or message me on Twitter/LinkedIn in case of any questions, doubts, ...
Basic Concepts | FrozenLake | Deep Reinforcement Learning
Просмотров 1,1 тыс.2 года назад
Reinforcement Learning is a paradigm of Machine Learning Algorithms, that work on the principle of Learning by Doing. Reinforcement Learning uses several basic ideas about the Agent, Environment, States, Actions, Observations, Policy and Value Functions. The complete setting of Reinforcement Learning along with these concepts are discussed. Feel free to leave a comment or message me on Twitter/...
Custom Mobile Robot | Part - 4 | ROS Learning Series
Просмотров 9492 года назад
This video is Part 4 of the ROS Learning Series. In this video, we discuss how to create a Custom Mobile Robot in ROS. Mainly, the dynamics involved in building the URDF file are discussed. The simulated robot is a differential drive robot with a laser sensor. Feel free to leave a comment or message me on Twitter/LinkedIn in case of any questions, doubts, suggestions or improvements. Twitter: t...
ROS 2 | Part - 6 | ROS Learning Series
Просмотров 6872 года назад
This video is Part 6 of the ROS Learning Series. In this video, we discuss ROS 2, and it's differences with ROS1. We discuss all the different commands in ROS 2 and run a simple Dolly example in ROS2. Feel free to leave a comment or message me on Twitter/LinkedIn in case of any questions, doubts, suggestions or improvements. Twitter: MahnaSakshay LinkedIn: www.linkedin.com/in/saksha...
MoveIt! Robot Manipulators | Part - 5 | ROS Learning Series
Просмотров 2,7 тыс.2 года назад
This video is Part 5 of the ROS Learning Series. In this video, we discuss how to simulate Robot Arms in ROS, using the ROS Package - MoveIt! We create a simple Motion Planning example using Panda Robot Arm and then simulate Grasping in a Pick and Place scenario. Feel free to leave a comment or message me on Twitter/LinkedIn in case of any questions, doubts, suggestions or improvements. Twitter...
ROS Concepts | Part - 3 | ROS Learning Series
Просмотров 6972 года назад
This video is Part 3 of the ROS Learning Series. In this video, we discuss the different ROS concepts, like ROS Graph, Publisher-Subscriber, Services and Actions. We also simulate an Obstacle Avoidance based TurtleBot3 AI using the concepts discussed. Feel free to leave a comment or message me on Twitter/LinkedIn in case of any questions, doubts, suggestions or improvements. Twitter: twitter.co...
Python for AI | Live Session
Просмотров 3032 года назад
The recording of the Live Session: Python for AI. The session covers What is AI and Search Algorithms in AI. Also, the Binary Search algorithm is also implemented in Python, introducing the basic concepts of Python required along the way. Feel free to leave a comment or message me on Twitter/LinkedIn in case of any questions, doubts, suggestions or improvements. Twitter: MahnaSaksha...
Simulating TurtleBot3 Robot | Part - 2 | ROS Learning Series
Просмотров 2,3 тыс.2 года назад
Python for AI Live Session, on 22nd April 2022 at 9.30 PM IST. Sign Up and then Register on this Link: www.lighthall.co/class/30791c3d-bbe4-4a4e-8357-319560dba59a This video is Part 2 of the ROS Learning Series. In this video, we discuss the different components of Mobile Robot: Localization, Mapping and Navigation, and simulate the TurtleBot3 Robot to see these components in action. Feel free ...
Reinforcement Learning | TurtleBot3 Robot | Motion Planning for Robots
Просмотров 4 тыс.2 года назад
Reinforcement Learning is a paradigm of Machine Learning Algorithms, that work on the principle of Learning by Doing. Q Learning is one of the most popular Reinforcement Learning algorithm. The algorithm uses Bellman Update Equations to plan paths given the start and goal positions. The algorithm has been demonstrated on the TurtleBot3 robot in ROS (Robot Operating System) based simulation. Fee...
Introduction to ROS | Part - 1 | ROS Learning Series
Просмотров 4,2 тыс.2 года назад
This video is Part 1 of the ROS Learning Series. This video introduces ROS (Robot Operating System), it's use cases and applications. Towards the end, installing ROS on a Windows system and running Gazebo and RViz is also demonstrated. Feel free to leave a comment or message me on Twitter/LinkedIn in case of any questions, doubts, suggestions or improvements. Twitter: MahnaSakshay L...
DWA Planner | Husky Robot | Motion Planning for Robots
Просмотров 7 тыс.2 года назад
DWA Planner is a popular local path planning algorithm. The algorithm is quite efficient and used as a default planner in the ROS Navigation Stack. The algorithm utilizes robot kinematics to generate various different candidate paths, and then uses an optimization function to find the best trajectory to follow. The algorithm is discussed on the video and has been demonstrated on the Husky UGV r...
Virtual Force Field | Formula 1 Robot Car | Motion Planning for Robots
Просмотров 9862 года назад
Virtual Force Field | Formula 1 Robot Car | Motion Planning for Robots
Frenet Frames | Self Driving Cars | Motion Planning for Robots
Просмотров 4,6 тыс.2 года назад
Frenet Frames | Self Driving Cars | Motion Planning for Robots
RRT Planner | Spot Robot | Motion Planning for Robots
Просмотров 2,3 тыс.2 года назад
RRT Planner | Spot Robot | Motion Planning for Robots
Genetic Algorithm | UR5 Robot | Motion Planning for Robots
Просмотров 3,5 тыс.2 года назад
Genetic Algorithm | UR5 Robot | Motion Planning for Robots
A* (A Star) Search | TurtleBot3 Robot | Motion Planning for Robots
Просмотров 9 тыс.2 года назад
A* (A Star) Search | TurtleBot3 Robot | Motion Planning for Robots
Siamese Networks | Face Recognition | Computer Vision on Humans
Просмотров 9 тыс.2 года назад
Siamese Networks | Face Recognition | Computer Vision on Humans
DCGAN | Fake Face Generator | Computer Vision on Humans
Просмотров 1,5 тыс.2 года назад
DCGAN | Fake Face Generator | Computer Vision on Humans
Part Affinity Fields | Human Pose Estimation | Computer Vision on Humans
Просмотров 1,8 тыс.2 года назад
Part Affinity Fields | Human Pose Estimation | Computer Vision on Humans
Local Binary Features | Face Landmark Detection | Computer Vision on Humans
Просмотров 4282 года назад
Local Binary Features | Face Landmark Detection | Computer Vision on Humans
Haar Cascade | Human Body and Face Detection | Computer Vision on Humans
Просмотров 2 тыс.2 года назад
Haar Cascade | Human Body and Face Detection | Computer Vision on Humans
UNetXST | Camera to Bird's Eye View | Perception for Self Driving Cars
Просмотров 5 тыс.2 года назад
UNetXST | Camera to Bird's Eye View | Perception for Self Driving Cars
SFA 3D | 3D Object Detection | Perception for Self Driving Cars
Просмотров 2,6 тыс.2 года назад
SFA 3D | 3D Object Detection | Perception for Self Driving Cars
Multi Task Attention Network (MTAN) | Multi Task Learning | Perception for Self Driving Cars
Просмотров 1,1 тыс.2 года назад
Multi Task Attention Network (MTAN) | Multi Task Learning | Perception for Self Driving Cars
KITTI 3D Data Visualization | Homogenous Transformations | Perception for Self Driving Cars
Просмотров 5 тыс.2 года назад
KITTI 3D Data Visualization | Homogenous Transformations | Perception for Self Driving Cars
Deep SORT | Object Tracking | Perception for Self Driving Cars
Просмотров 15 тыс.2 года назад
Deep SORT | Object Tracking | Perception for Self Driving Cars

Комментарии

  • @bahaeddinehemmemCHAREN
    @bahaeddinehemmemCHAREN 13 дней назад

    Khouya l hendi lizoum

  • @ARkhan-xw8ud
    @ARkhan-xw8ud 16 дней назад

    triplet loss is also used for the same

  • @granatapfel6661
    @granatapfel6661 16 дней назад

    Can you help with the bev data of the dataset?

  • @sorenadashti4333
    @sorenadashti4333 23 дня назад

    how can I record for dataset

  • @chaosNinja790
    @chaosNinja790 27 дней назад

    Thank you very much. You really helped me. Godsend

  • @SatheeshS-v3b
    @SatheeshS-v3b Месяц назад

    Really helpful sir. Do you have any idea about these same trajectories using MATLAB?

  • @SatheeshS-v3b
    @SatheeshS-v3b Месяц назад

    Mind blowing Work!

  • @boukermouchemohammed8729
    @boukermouchemohammed8729 Месяц назад

    Thanks

  • @The_biggest_G.O.A.T
    @The_biggest_G.O.A.T Месяц назад

    Sir I am making a facial recognize attendance system using Siamese network the capture image's train successfully but when I want to track image it's not recognize the registered person can you please help me with this I'll pay charge's too but please don't ignore my comment I'm in trouble since 2 day's

  • @MobinaAmrollahi-k7j
    @MobinaAmrollahi-k7j Месяц назад

    You're videos are truly gems! Having the codes in front of you and explaining them line by line, no course will do this!

  • @counterside9576
    @counterside9576 2 месяца назад

    Plz help me there is some problem in the root directory to the dataset

  • @AnmolKumar-so8lh
    @AnmolKumar-so8lh 2 месяца назад

    One of the best 👍🏿

  • @karthickkuduva9819
    @karthickkuduva9819 3 месяца назад

    Multitask learning and Vision transformer are same ?

  • @user-hi2hb2ny2p
    @user-hi2hb2ny2p 4 месяца назад

    Good explanation, thanks, upvoted

  • @nayanrajannavar
    @nayanrajannavar 4 месяца назад

    WHAT IS THE INPUT WE SHOULD WE GIVE TO IT TO RUN THE CODE

  • @nimetullaherensarioglualum6843
    @nimetullaherensarioglualum6843 4 месяца назад

    Great video man, keep up the good work

  • @MuhammadUsman-t4z
    @MuhammadUsman-t4z 5 месяцев назад

    Absolutely Amazing

  • @abrahamyalley9973
    @abrahamyalley9973 5 месяцев назад

    how do i combine this with a global path planning algorithm like a star for obstacle avoidance

  • @abrahamyalley9973
    @abrahamyalley9973 5 месяцев назад

    how do i set the astar algorithm as my global path planning algorithm

  • @SparshGarg-n8e
    @SparshGarg-n8e 5 месяцев назад

    Awesome, thanks!

  • @a.t10
    @a.t10 5 месяцев назад

    it is a very useful content. thank you everything.

  • @edupedika
    @edupedika 6 месяцев назад

    isit possible to combine astar and rrt for mobile robots to build an hybrid

  • @edupedika
    @edupedika 6 месяцев назад

    Not reaching the goal ?

  • @shalinikumari1811
    @shalinikumari1811 6 месяцев назад

    thankyouu

  • @theboss73104
    @theboss73104 6 месяцев назад

    Bruh how to track a recognised person? With his name

  • @PIYUSHTAILORstillalive
    @PIYUSHTAILORstillalive 7 месяцев назад

    I was thinking to make robotics channel and then this guy with already 78 videos. Are you looking for collaboration?

  • @kordou
    @kordou 8 месяцев назад

    thank you for this nice course. is there any way to get an efficiency on the test data as a value also in the jupyter notebook ?

  • @jumanaal-qarei8667
    @jumanaal-qarei8667 8 месяцев назад

    should I copy the code and paste it in order in one py file? or what please clarify

  • @aasheesh6001
    @aasheesh6001 8 месяцев назад

    Thanks bro for this.

  • @luuminhquan8255
    @luuminhquan8255 8 месяцев назад

    Unable to download the weights. Can you pls help.

  • @pocopoco3468
    @pocopoco3468 9 месяцев назад

    I'm trying to make a LFR(Line follower robot) till now I have made it to run on Balck and white line, all complex and simple turns, line discontinue etc. But I'm facing problem in loops, how to make a LFR to detect loop?

  • @llegenda-r3c
    @llegenda-r3c 9 месяцев назад

    I am learning JavaScript can I make using tenserflow js

  • @sabzimatic
    @sabzimatic 9 месяцев назад

    ruclips.net/video/h5vJjWGCtsI/видео.html So the graph at above time in the video is showing continuous joint angles along with r,p,y. Can there be an instance in time (0 to 1 second) in the above graph where that particular set of joint angles (and r,p,y) are not feasible, meaning a singularity condition appears ? in between good effort on the topic and videos.

  • @UT_BHUTAN
    @UT_BHUTAN 10 месяцев назад

    can i use a pretained model and make an application where i will allow students to register their face and once they are done, they can login to the app and start verifying their face. I want the app to work in way whereby i need not have to take time to collect facial data of every students in the class. I want the data collection to be done while registration of the student to the app.

  • @vikasp-j1x
    @vikasp-j1x 10 месяцев назад

    Brother can you suggest me any resources for doing the same , i wanna to implement my path planning in ros like you did , but i don't know how to start . I know the algorithm and implemented it in cpp without ros but i don't know to integrate like you did can you help me brother

    • @vikasp-j1x
      @vikasp-j1x 10 месяцев назад

      i want some resources to refer

  • @aminullah2666
    @aminullah2666 10 месяцев назад

    How the Truncation is calculated during annotation, is it based on visible pixel or it is from actual 3D box?

  • @man9mj
    @man9mj 10 месяцев назад

    Excellent effort, thanks for sharing.

  • @SonyaKrot
    @SonyaKrot 10 месяцев назад

    Tell me, I did everything as you said, but the following error is displayed, I haven’t been able to solve it for a long time, what can I do? :/opt/ros/noetic/share/MLinROS/car_ws/src/perception/scripts$ python 3 line_follower.ру Traceback (most recent call last): File "lane_follower.py", line 5, in <module> from prius_msgs.msg import Control Module Not Found Error: No module named 'prius msgs'

  • @muhammadtehreem4146
    @muhammadtehreem4146 10 месяцев назад

    pp_msgs is not present at lerp_motion_planner

  • @ashraykhosin4162
    @ashraykhosin4162 11 месяцев назад

    model_history = model.fit(dataset['train'].repeat(), epochs=EPOCHS, steps_per_epoch=STEPS_PER_EPOCH, validation_data = dataset["val"], validation_steps=STEPS_PER_EPOCH// 10, callbacks = callbacks) ValueError: Unexpected value for `steps_per_epoch`. Received value is 0. Please check the docstring for `model.fit()` for supported values.

  • @SudipBiswaseskysudip
    @SudipBiswaseskysudip 11 месяцев назад

    I have a environment with multiple continuous action what should I do.

  • @a.k.aproxi5442
    @a.k.aproxi5442 11 месяцев назад

    how can i use it for ROS2?

  • @sarthaksinha6588
    @sarthaksinha6588 11 месяцев назад

    bhai isme error bhut ha

  • @jimj2683
    @jimj2683 11 месяцев назад

    Why has nobody collected data from the real world? You could attach a pole with a downward-facing camera on top of a bunch of teslas and drive around collecting data. Then you have all the ground truth you need for making 360 parking cameras much better.

  • @_shikh4r_
    @_shikh4r_ 11 месяцев назад

    Good Job! Please upload more.

  • @vaishalikharola8629
    @vaishalikharola8629 Год назад

    But why we can use semnatlcly

  • @sdfasd8853
    @sdfasd8853 Год назад

    add subtitles.

  • @sasanmir8122
    @sasanmir8122 Год назад

    My god you are amazing plz plzzzz make more videos

  • @mugundans2004
    @mugundans2004 Год назад

    Hey bro, I watched your video from freecodecamp, such a intresting session, a big salute to your work brother, keep posting many videos, kindly post some videos related to ros2 and usage of ros2 in autonomous vehicle system

  • @abrahamyalley9973
    @abrahamyalley9973 Год назад

    hello, i am new here and wanted to know what language are you using for the tutorial , c++ or python