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good job bro also love your content

It is very simmilar with explanation of evolution.

Great video 👍

We did Q Learning

I really like the video and how you explained everything really easily. If I wanted to learn how to create a walking robot on my own where would I start?

Next step: The Robot Learns to make a partner

This video per se, is a masterpiece.

take the sticks and table off. or design a robot thats made for walking instead of uselessly tilting a plate.

maybe add sinewaves with difrent frequencies like in a forier transform

Great work! What software did you use for the simulation?

Nice project. Rubber pads in the legs contact surface may allow for greater speeds... Shifting the wave form towards the ground may reduce 'no contact' time... Using NEAT to 'punish' unwanted behaviours (long no contact times, wrong movement direction, etc) may generate better solutions...

Perhaps designing a sequence of stages with different constraints on evolution would yield interesting results - for example, if you first ran several generations with the fixed sine wave phase, then took the best offspring as starting points for another several generations in which the phase is allowed to vary, and maybe another factor is locked instead. Different orders of the same constraints could lead to wildly different solutions - it would basically be a genetic algorithm of genetic algorithms, simulating a slowly changing environment... From that last thought, I wonder if the specific constraint changes could also be determined algorithmically in a way that simulates each generation's impact on the environment...

Great video! Really enjoyed this project. Curious what your background is? Did you have much programming experience or previous genetic algo experience before beginning this? How long did this all take you?

JD Robotics, Such a cool project! I am a fan of genetic algorithms myself, have you taken a look at Real-Coded Genetic Algorithms (RCGAs)? They are similar to Binary-Coded Genetic Algorithms (BCGAs) but use real values in their genes instead of binary. There are a handful of cool crossover events as well that you can do with real values. I don't know if it would have changed the results of your simulations but if you are ever interested it could be fun to see the difference in effectiveness between the two types of genetic algorithms. I had initially brought this up to argue your crossover event. My thought was that representing floating point values with binary could cause crazy values to result when your crossover splits up a mantissa. This is not the case! I worked an example out to myself and it actually results in very reasonable values! I'll keep my comment here though just in case you have not seen RCGAs before! (And it would still be cool to see a comparison between RCGAs and BCGAs on a real bot), I have not done extensive work with comparing BCGAs and RCGAs so I do not know if there will be a difference if applied to the same problem. best, random internet commenter and new subscriber

Nice project ! I think a couple good changes would be, - Add rubber ' feet' the lack of traction seems to be hurting the performance. - perform the tests for more iterations with perhaps a larger population? I'm not sure what your population size was but most videos I watch on these topics have between a 100 and 1000 members and test for 1000 to 10 000 iterations. If you do plan on testing, in simulation, what geometry would be best, you should combine that with finding the optimum gate. As geometry and gate would be linked. This will increase simulation complexity however. If you can perform these simulations on a campus computing system, I would suggest that. Looking forward to your next video on this!

Very cool!

Rather than do a simple sine wave, have you considered using a random noise pattern and then doing an inverse FFT to drive the servos?

it needs shoes

Hey can you share a link to your code, this is perfect for me, i have built a worm/snake like robot that uses only 2 motors for x and y directions i'd like to see some optimum solution to it's motion

It would be interesting to see if replacing the basic sine wave with a Fourier series of maybe 5 terms would yield better results. This emulates the nature of real-world gaits well, which are usually periodic and smooth, but not quite sinusoidal.

I think if you increase the number of generations, you will get better results. GA is very sensitive to local minimum and more generations give it the chance to escape from this through mutation.

Good video 📸

Superb content, great work

Regarding period selection: instead of choosing random real numbers, choose a random natural multiple of the base period (2, 5, 15, etc.). This will ensure all movements are synchronised within the desired timeframe. Finally, regarding the selection of an alternate function: because your solution is defined to be periodic, Fourier proved that any solution will be of the form of a summation of sine waves scaled and shifted across all frequencies. As such, you could simply include more sinusoids at higher frequencies for each DoF.

Very cool! How did you generate the footage of multiple bots at once? (eg. at around 7:12) I'd be very keen to see how you go if you decide to optimize for geometry as well as gait. I also wonder how modifying the friction between the legs and the ground would affect the speed 🤔 From the footage at the end (eg. 16:33), it looks like there's quite a bit of slipping, though it's difficult to know whether that helps or hinders the movement. Keep it up!

This is amazing. Great content. Can't wait to see more.

Imagine the horror of your stewart platform crawling in your room at night like a water bug lol.

This was so cool, very well explained

put rear-most leg into soft contact with ground, lift front up fully so it pivots up on the rear legs, lower rear to contact frame, drop front. repeat. is basically falling forwards by altering the pivot points. It's not generational learning, but I wonder if it's learned forwards speed can physically surpass that basic movement sequence? (It has to not bind it's gantry while doing it obviously)

Very nicely put together video!

This is awesome.

I'd be interested in seeing a tutorial on how you used gazebo. How did you enter your robot, duplicate your robots and simulate your robots?

Very impressive!

You mentioned a problem with the joints. Instead of Ball and Socket, or using multiple ball bearings, have you thought about using a Flexture Joint? Or a Rolling Contact Joint? You can get either to rotate around 1, 2, or even 3 axis. Flextures tend to have a low range of movement, but rolling contact joints are pretty flexible as well as compact. Here's a video from Breaking Taps where he's using them to create bird legs. ruclips.net/video/TQiLLcumqDw/видео.html&ab_channel=BreakingTaps

God damn that transition at the end

Nice visuals and explanation

Are you going to release the design files and code?

I would use that robot to control a hydrolaser to cut organically shaped material that is traveling along a set plane. Positioning needs to be fast and fairly accurate and able to withstand whatever forces applied from the hydro laser

There is one problem I can see for walking. True to the leg geometry, the legs will need to slip which is for the most part undesirable for a walking robot and with the legs slipping you will be limited to clumsy and inefficient walking. It should be doable though.

Awesome video! You have a really smooth and easy to follow style!

Dude. You rock 🔥

This is awesome! And makes me think I should relearn trigonometry because apparently I don't remember/understand anything

I like the video but whats wrong with your voice

nice explanation, amazing visualization great work, and for the suggestion I wonder what if you flip the robot upside down, will it jump and walk

U r the best i think u before it. Can u make a full tutorial on it..

Is it possible to also replace the top plate joint by the ball and magnet joint as the lower plate?

Great visualization and awesome explanation of the inverse kinematics.

so cool is it gonna be open source by any chance

make an autonomus rc car 3d printed

Very nice but seems a bit wobbly - this might not be of a concern for a walker but for other applications it's usually unwanted characteristics.