u/Xerd-R

Hi Everyone, I used imitation learning to train a small MLP as the control policy for my custom hexapod robot dog. I recently got a masters degree in applied machine intelligence and have been looking for a suitable platform to create a neural network from scratch.

Once I got a working controller with Inverse Kinematics solver, I decided to implement imitation learning in a simulation enviroment to see if it would replicate the IK solvers behavior and it worked!

I haven't tried running the neural network on ESP32 yet but I saw on Arduino sub reddit someone managed to run a 30 million parameter LLM on one so I am sure my 30k parameter controller network can work on it as long as I manage to pull it off myself.

I have been seeing a lot cool robotics projects here but not much on the simulation side, how often do you use simulations for development? what simulations do you use for which task?.

I share all my scripts in my GitHub, if you are interested you can find them from the link below.

https://github.com/serdarselimys/

For this project you can download the script directly from the link below in case if you dont want to watch the video

https://github.com/serdarselimys/Pybullet-ImitationLearning

If you watch the video and have any feedback please share them, either here or on the video comments section, I would love to get some feedback for parts that I can improve.

Hi Everyone, I used imitation learning to train a small MLP as the control policy for my custom hexapod robot dog. I recently got a masters in applied machine intelligence and have been looking for a suitable platform to create a neural network from scratch. We were heavily taught transfer learning for classification and never had a chance to create a working neural net from scratch.

Once I got a working controller with Inverse Kinematics solver, I decided to implement imitation learning on it to see if it would replicate the IK solvers behavior and it worked!

Its trained with a modest 2gb sized dataset (compared to LLM and CV datasets) which I generated by capturing robots input commands and output joint angles in, again, PyBullet simulations. I did experiment with varying the network size by half, double and quadruple but it didnt have much effect on trained MLPs performance, roughly 1 degree mean error compared to base IK solver output angles. Next I plan to vary the data capture logging rate by doubling it rather than just extending the capture time to give it more data resolution. I also plan to compare different types of networks basic MLP vs LSTM, Transformer, RNN etc.

Next I plan to implement reinforcement learning to create a helper network that will modify the base MLPs behavior. I am having trouble with my Robot climbing up inclines, I think that would be the best experiment for training the helper neural network. I also want to create another helper network to replicate the behavior of current analytics based body leveling mode.

What are you opinions of my approach? Is creating one base walking controller network with additional task specific modifier networks is a good idea?? I am will try to implement these control methods in ESP32 hence I am trying to build multiple small networks to be fired up on demand in order to allocate limited compute resources efficiently.

I share all my scripts in my GitHub, if you are interested you can find them from the link below.

https://github.com/serdarselimys/

Hi everyone, I just uploaded my first tutorial video on YouTube and wanted to share it here to get your opinions about it.

its very short and simple tutorial for the subject matter but I figured since I shared my scripts anyone who is interested would like consult an Ai chatbot for their specific questions and the main point of the video is the briefly explain the main concepts and how it all works within PyBullet. if you have free 7 minutes, I would appreciate your thought and opinions about the video so I can improve for upcoming videos.

I know Genetic Algorithms are a bit yesteryears news but I remember watching a video about them on 2minutespapers YouTube channel years ago and since the moment I loaded my robot to PyBullet I wanted to try to implement the technique myself on my own project. Thats why its the subject of my first tutorial video.

I am also sharing the links to my GitHub repo for the scripts here as well in case if you dont want to watch the video but still interested in implementing genetic algorithm for robotics in PyBullet.

PyBullet Genetic Algorithm repo: https://github.com/serdarselimys/PyBullet-GeneticAlgorithm

PyBullet HexaDog ZBD control repo: https://github.com/serdarselimys/HexaDogZBD-PybulletDemo

For the next tutorial I am planning to cover Imitation Learning, again in PyBullet. Do you think thats an interesting subject?? I have been seeing a lot of videos on social media about manual laborers, mostly, textile workers are being made to wear POV cameras to capture their work to be used to train Neural Networks. I figured a tutorial explaining how digital movements are copied over to neural networks would be interesting.

Hi everyone, as I started telling and showing my robot to people around me I noticed every time I tell people I built a robot they ask me "what it does" and a simple answer of "it walks" is not a sufficient answer it turns out, so I have been working on adding different emotes to it to entertain the general audience. You can check out the Emotes from the video above

Until I get it to talk and listen to voice commands with LLM integration, emotes are all I got. Let me know what other types of emotes you would want to see it do?? I am running out of Ideas, with six legs you would think I could come up with some better ones but so far my only original one is the Battle Mode, which is the bigger robot in the thumbnail.

Also I uploaded my first GitHub repository for the Robot. If anyone is interested you can download it following the instruction on the read me file and control the robot in PyBullet. The link for the repo is in the video description.

I am currently working on a short video tutorial for Optimizing the robots walking in Pybullet using genetic advancement, hope fully I will be done with it by the end of Tomorrow (Unlikely) and upload it to YouTube over the weekend.

Thank you all for the upvotes on my first post here, they have been quite uplifting and motivating to continue working on the robot. Its nice to get recognized by people working in the same field.

Follow up to : https://www.reddit.com/r/arduino/comments/1uv6p5d/my_hexapod_robot_dog_indoor_walking_test/