/robowaifu/ - DIY Robot Wives

Advancing robotics to a point where anime catgrill meidos in tiny miniskirts are a reality.

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Bipedal Robot Locomotion General Robowaifu Technician 09/15/2019 (Sun) 05:57:42 No.237
We need to talk about bipedal locomotion. It's a complicated topic but one that has to be solved if we are ever to have satisfyingly believable robowaifus. There has surely already been a lot of research done on this topic, and we need to start digging and find the info that's out there. There are some projects that have at least partial robolegs solutions working, but none that I know of that look very realistic yet. We likely won't come up with some master-stroke of genius and solve everyone's problems here on /robowaifu/, but we should at least take a whack at it who knows? We certainly can't accomplish anything if we don't try.

I personally believe we should be keeping the weight out of the extremities – including the legs – while other anons think that we should add weight to the feet for balance. What's you're ideas anon? How do we control the gait? How do we adjust for different conditions? What if our robowaifu is carrying things? What about the legs during sex? Should we focus on the maths behind MIP (Mobile Inverted Pendulum), or is there a different approach that would be more straightforward? A mixture? Maybe we can even do weird stuff like reverse-knee legs that so many animals have. Robofaun waifu anyone? What about having something like heelys or bigger wheels in the feet as well?

I'm pretty sure if we just put our heads together and don't stop trying, we'll eventually arrive at least one good general solution to the problem of creating bipedal robot legs.

ITT post good robowaifu legs

>tech diagrams sauce
>>12582 Will do anon, thanks for link.
how soon we will have a bipedal robot that can imitate humans
>>13439 when the geniuses stop focusing on just the legs and finally figure out you cant have bipedal motion without fucking ears and start using gyroscopes
>>13447 How would you implement them?
>>13451 same way the human body does a feedback loop making continuous micro adjustments autopilots already do this with stabilizers, but thats easy for something with a plane perpendicular to gravity, parallel planes are in a league of their so dont bother until synthetic musclefibers become a thing
> (>>16593 - information & videos -related)
>Energy optimization during walking involves implicit processing [1] >Gait adaptations, in response to novel environments, devices or changes to the body, can be driven by the continuous optimization of energy expenditure. However, whether energy optimization involves implicit processing (occurring automatically and with minimal cognitive attention), explicit processing (occurring consciously with an attention-demanding strategy) or both in combination remains unclear. Here, we used a dual-task paradigm to probe the contributions of implicit and explicit processes in energy optimization during walking. To create our primary energy optimization task, we used lower-limb exoskeletons to shift people's energetically optimal step frequency to frequencies lower than normally preferred. Our secondary task, designed to draw explicit attention from the optimization task, was an auditory tone discrimination task. We found that adding this secondary task did not prevent energy optimization during walking; participants in our dual-task experiment adapted their step frequency toward the optima by an amount and at a rate similar to participants in our previous single-task experiment. We also found that performance on the tone discrimination task did not worsen when participants were adapting toward energy optima; accuracy scores and reaction times remained unchanged when the exoskeleton altered the energy optimal gaits. Survey responses suggest that dual-task participants were largely unaware of the changes they made to their gait during adaptation, whereas single-task participants were more aware of their gait changes yet did not leverage this explicit awareness to improve gait adaptation. Collectively, our results suggest that energy optimization involves implicit processing, allowing attentional resources to be directed toward other cognitive and motor objectives during walking. >Humans Are Designed to Think While Walking [2] >One of my favorite things to do when I am on vacation is hike in the mountains and take in as much scenery and contact with wildlife as possible. The former requires that I stay in good enough physical conditioning that I can achieve 15+ miles of mountain hiking per day. Therefore, when I am not on vacation, I go for a two-to-four-mile run every day before breakfast. That morning routine keeps me in physical shape and prepares me to undertake the research and writing projects for that day. Our problems are much, much simpler than God's were when He was designing us human beings with all our facilities, including these two. However, I'd say it's a good model for us to follow. After all, robowaifus should be able to talk with us about different things; like being young newlyweds while she's cooking a meal for us upstairs at the pub, right Anon? :^) Maybe Carver Mead's (et al) Neuromorphics can help us all out with this a bit. To wit: push the computation out to the edges of a [robowaifu's] system[s]. That way, while the 'autonomous' things are happening, her central-core computation mesh can be freed up to talk with us about important things. 1. https://pubmed.ncbi.nlm.nih.gov/34521117/ 2. https://reasons.org/explore/blogs/todays-new-reason-to-believe/humans-are-designed-to-think-while-walking >=== -minor fmt edit -add 'important things' cmnt
Edited last time by Chobitsu on 07/25/2022 (Mon) 22:07:22.
I think this general approach should be applicable, it is validated in real-life swiss quadruped robot [1] and in simulated [2] & real bipedals [3]. Compared to less-validated approaches it's a clear winner. You don't have to implement it in main AI, it's better if it runs on a small low-latency auxilary NN. It doesn't require too much compute or data, and the gait can be tuned via adding energy expenditure & smoothness terms to the loss. You can also include mocap data and tune the model on it for humanlike gait. 1. https://leggedrobotics.github.io/rl-blindloco/ https://www.youtube.com/watch?v=8sO7VS3q8d0 2. https://www.youtube.com/watch?v=hx_bgoTF7bs 3. https://techxplore.com/news/2021-04-robot.html
>crosslink-related (>>17989)
>(conversation-related >>18421, ...)
> (crosslink related : >>20777) Primitive 'walking' smol android.
>>17064 >Learning Quadrupedal Locomotion over Challenging Terrain These are great lengths. It got me thinking about something I would love to have besides a robot waifu. A ostrich runner I could ride on like a hirse. I would set it up to have a roll cage on top and have a body harness inside the cage because you know the thing will trip every so often and with a harness it wouldn;t be a problem. ANother addition could be a front extra leg. "If" it starts to trip, and it will eventually, it sticks out the front leg and rolls the robot to the side. That way you don;t face plant but sort of roll into the fall. So I look up trying to find how much energy a ostrich uses to run. I can't imagine it's as much as a horse(746watts) because they are heavier. I found a link and a set of papers on ostriches. This lady did a thesis on them running. https://www.scienceinschool.org/article/2011/ostrich/ and two papers. One one the ostrich and one on the energy needed for Men, horses and ostriches to walk.
Only got one paper here's the other Correction above "these are great LINKS..." and damn my typing is so bad and this little box I can't see my mistakes. Sigh.
Here's some thinking out loud about walking and the steps needed to program this or "a" numerical structural system to make this work. A strategy. So as I walk about, I started thinking about what I'm doing. It appears, to me, that walking is sort of a natural preprogrammed act where the muscles mostly know what to do. Brain tells body go here, go there, it goes here, goes there. So I started thinking about how we could do the same. I came up the idea that with small amounts of data passed to the muscles we could get good movement. My assumptions are we are using micro-controllers to control each muscle, with some extra processing power for each muscle. The first step is the brain makes a "map" of the terrain in front of it, what speed it is going at and then where it needs to step for that speed or terrain. I watched a Jim Keller interview with Lex Fridman and Keller said that this sort of distance measurement was trivial. In other words using two eyes you can tell where something is like the floor and how far away. He should know, he's a legend at AMD and Tesla, designing chips for...everything. So let's take his word for this, (yes there are likely to be complications but let's ignore for now). We will assume finding a place to step for the waifu is not big deal. A simple table of sorts could be built up of how far a step is depending on speed it wants to go and using that it maps where a good place to step is. So now we have that, then, we need a vector to this place. Now a leg, thigh, foot, movement is going to be constrained to how they can bend so if the brain sends a start moving vector(a angle for the foot to move AND a velocity), a end point to go to, then this set of vectors from the brain could be interpreted by ALL the muscles in the leg. Each one knows that to move here or there, it must act in a certain way. So with this one vector based on, move this way x, this way Y and this way Z, plus a speed, plus the end point, each muscle can work on its on to add up to this end point. So you have, (Each 2 bytes(16 bits) giving us 65,536 different values or postions) A starting direction for foot movement, x,y and z. If you need to step over something it will have a high value for "Y". It will pick the foot up high.(6 bytes) A velocity point for x,y and z, how fast to move(two bytes x, two bytes Y and two bytes z) (6 bytes) End point (two bytes x, two bytes Y and two bytes z) (6 bytes) and a foot position x and y for how the foot needs to land on the ground.(4 bytes) (22 bytes total) This will create a vector that tells the foot, leg, thigh, hip how far it is to lift the foot, how fast and what direction x,y,z. This data is really just where the foot moves. What direction and how fast to move in that direction, where it is to move the foot to and the position of the foot when it lands. All the muscles have to do a certain task to do this and they "know" what to do, they do their part by only feeding them foot movement data. Another thing I think that would be needed to give the waifu a real strong grasp on what to do, is to feed the muscles a body position based on the body mass point at the shoulders and the hip AND a velocity vector x,y and z of what the hips and shoulders are doing in respect to movement. I think these two measurements could really add a lot to it's position awareness with a small amount of data being passed. In this case. shoulder x,y,z position(6 bytes) shoulder x,y,z velocity(6 bytes) hip x,y,z position(6 bytes) hip x,y,z velocity(6 bytes) (two feet, 40 bytes x 2, so 80 bytes total)for feet and body in all. At 50KBs with 80 bytes, let's add in some error correction and maybe some other stuff so make it 500 bytes just to throw a number at it and you could do this a 100 times a second or every hundredth of a second. That's fairly good at a really slow network speed, though I would like to see the time interval smaller and kick the transfer speed up a little. It worth noting that if each processor can figure out it's moves on this small set of data it doesn't need continuous data streams. Only one set for each step. The walking models, that say they are successful, say they add refinements for the last part of the step so you could send a start and then small refinements as it continues through the step with way, way, less data than 500 bytes every 1/100 of a second. There's also two paths that could be followed. The main brain could figure out the proper step pattern for a specific body position and just send the 22 bytes foot movement step, velocity vector and end point to the muscles to walk. With each muscles processor figuring the actuation needed to preform that specific movement. Or it may be that some combination that changes depending on circumstance is used. Where sometimes the muscles get body data, (the shoulder, hip), positions and sometimes they just get foot movement data. I was pondering this and just decided to jot down what I was thinking.
A good link that might later become valuable to train waifus. The WILDTRACK Seven-Camera HD Dataset (repack) This is a dataset of people walking through a square recorded on camera. If analyzed for joint movement and then programmed into the waifu it could show it what it needs to do to walk. Difficult, but a good resource if you know what to do with it. 60GB large but is a torrent file so easy to download. https://academictorrents.com/details/6d5542b0d245ff4d37680f67f2fb96750e6d8c60
>>21602 This is really great & interesting stuff Grommet. I hope to have a long conversation with you about such details before too long. Cheers! :^)
Here's an old concept that's still pertinent for us today, /robowaifu/ : >ZERO-MOMENT POINT — THIRTY FIVE YEARS OF ITS LIFE abstract: >This paper is devoted to the permanence of the concept of Zero-Moment Point, widely-known by the acronym ZMP. Thirty-five years have elapsed since its implicit presentation (actually before being named ZMP) to the scientific community and thirty-three years since it was explicitly introduced and clearly elaborated, initially in the leading journals published in English. Its first practical demonstration took place in Japan in 1984, at Waseda University, Laboratory of Ichiro Kato, in the first dynamically balanced robot WL-10RD of the robotic family WABOT. The paper gives an in-depth discussion of source results concerning ZMP, paying particular attention to some delicate issues that may lead to confusion if this method is applied in a mechanistic manner onto irregular cases of artificial gait, i.e. in the case of loss of dynamic balance of a humanoid robot. >After a short survey of the history of the origin of ZMP a very detailed elaboration of ZMP notion is given, with a special review concerning “boundary cases” when the ZMP is close to the edge of the support polygon and “fictious cases” when the ZMP should be outside the support polygon. In addition, the difference between ZMP and the center of pressure is pointed out. Finally, some unresolved or insufficiently treated phenomena that may yield a significant improvement in robot performance are considered.
>OpenWalker >Framework Architecture >1.1 ProblemStatement >Biped and humanoid robots are complex systems composed by a large number of actuated degrees of freedom and various sensors that provide the requirements for the complex process of walking. Due to such complexity and number of components, in the past decades, the community of humanoid robots has developed several robot architectures for different purposes and applications. All these robot architectures, ranging from small-size hobby robots to giant manned walking machines, share some anatomical similarities developed through years of work in this field. Nevertheless, the task of coordinating the information generated by all the sensors and actuators in humanoid robots poses a complex software problem which has been approached with different paradigms. Consequently, a large variety of different software frameworks has been created which, in most of the cases, are intrinsically connected to the robot hardware that they were designed for. This hardware dependency makes it difficult to develop software packages which can be reused by other teams. As a result, the robot developers must continuously re-implement essential software modules/components to comply with the requirements and restrictions of their system, slowing down the progress of biped and humanoid robotics. In particular, two of the most essential components required by this type of robots are the balance and walking controllers. Software will be the key to solving robowaifu bipedal locomotion. Everything is an interdependent-system of course, but without good software, our robowaifu's hips, legs, & feet are simply mannequins.
I suggest researching prosthetics. They are the field for bipedal movement eith the highest research. The most annoying part is the knees and ankles.
>>21776 Great advice Anon, thanks! The OP opener image ITT is a high-tech prosthetic leg.
>>21810 Yeah I noticed. That leg is the prlsthetic that started me on this resesrch rabbit hole. That and the prosthetic a guy did for his missing fingers. 100% mechanical. Wich is impressive. Some stuff I think can be done mechanically that don't need actuators. Atleast that is my theory.
>>21811 >Some stuff I think can be done mechanically that don't need actuators. Atleast that is my theory. That's actually a very solid engineering approach to problems in general, Anon. Anything we can do/use to simplify the systems we're working with is a big plus for us in numerous ways.
>>21813 Been thinking about this a lot. I wonder if mechanical systems like windup clocks or gravity feed systems can be used. They have an input output binary like in digital systems that might help bring cost down possibly.
>>21849 Just like all engineering, it's a series of choices each involving tradeoffs. We've basically 'coalesced' around batteries + BLDC actuator systems because they--in effect--bring the greatest benefits for the least costs. That being said, once the era of robowaifus begins, then I doubt not that many very clever men will find ways to further-optimize her systems, which very likely may include numerous mechanical contrivances. However it goes, it's going to be a highly-interedasting field to come! :^)
>>21811 Technically, bipedal motion can be defined by hip and trunk actuation. Humans walk as pendulums which use our muscles to pump the oscillation. Researching passive dynamic walking will help you. >>21813 Indeed, one thing that every engineer learns through every success and failure is simplicity is the absolute king. >>21849 You're well on your way with that way of thought. Human walking utilizes Both gravity and stored potential energy through our elastic ligaments, which can be thought of as a windup mechanism. Using clever designs and elastic elements like springs and rubber bands is actually essential for approaching human walking efficiency. Picrel is an old walking mechanism that relies on gravity for power with compelety passive knees preventing the feet from tripping it over. There are many flaws I can see at a glance, for a fun activity, try annotating the design with how you'd improve it. Analysis for the sake of improvement can be a valuable way to quickly gain deeper understanding. An easy hint is that humans move our chests side to side while walking. Why waste calories moving a large mass? How does this lower overall caloric use in walking? >>21852 Watching this field has been enlightening and interesting indeed. Picrel 3 was what got me into the field many years ago. For more information on it: http://ai2001.ifdef.jp/mr1/mr1.html What brought you into the field?
Great video for learning from example https://yewtu.be/watch?v=nVC9D9fRyNU
>>21859 >Picrel 3 was what got me into the field many years ago. Interesting >For more information on it: >http://ai2001.ifdef.jp/mr1/mr1.html Thanks! >What brought you into the field? I've always wanted a robot friend since boyhood, plus AI was an interesting topic as well. But as an adult, it's the concern for the welfare millions of men abused by the Satanic machinations of the Globohomo that drives this passion regarding robowaifus. (>>14500) And very-specifically, it's for Anon that I'm working towards this robowaifu goal first and foremost. Normalfags already have metric boatloads of support systems haha. :^) But yeah, I always thought robots were cool long before I thought much about the waifu aspect of it.
>>21753 >ZERO-MOMENT POINT Yes really helpful!
>Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning This study investigates the use of deep reinforcement learning to train a miniature humanoid robot with 20 actuated joints to play a simplified 1v1 soccer game. The robot learned dynamic movement skills such as walking, turning, kicking, and fall recovery, as well as basic strategic understanding of the game. The agents were trained in simulation and transferred to real robots with minor hardware modifications and basic regularization of behavior during training. The resulting policy exhibited safe and effective movements while still being dynamic and agile, outperforming a scripted baseline in terms of speed and efficiency. Paper: https://arxiv.org/abs/2304.13653 Website: https://sites.google.com/view/op3-soccer
>>22224 Neat! Thanks RobowaifuChat-Anon, and welcome!
>>22224 Great, I hope we can do that when we need it. Mujoco: https://mujoco.org/
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I'm going to repost this from the short stack thread: http://davidbuckley.net/DB/index.htm This guy made a bunch of simple bipedal walker robots that might be useful for early robowaifus.
>>22542 Very cool, thank you Anon. Kinda reminds me of some of the droids from St*rwars.
>>22224 stop bullying him!!! D:
>>22688 Excellent find Anon! Looks very promising. They've managed to capture some fairly realistic human-like motions for a prototype. I'll be interested to see more technical information from this research group in the future. Thanks Noidodev. Cheers. :^)
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I know there is a mechanical thread , but what if the solution of the affordable robowaifu is in the Jansen walking mechanism? https://www.youtube.com/watch?v=C7FMIRfP1tk Changing the length of the links dynamically probably and finding the correct set of nodes could lead to something functional and aesthetic.
>I know there is a mechanical thread We even have one for monster waifus: >>10259 - good luck...
>>22728 I'm going to merge this thread soon into our Bipedal Locomotion thread, OP. Jansen mechanisms (and similar ones) have been discussed here on /robowaifu/ before. Allow me to agree with Noidodev, and wish you good luck Anon! Cheers. :^)
James Bruton showing the basics of bipedal robots and the challenges in another example: https://youtu.be/WJKhpGFg4uU - not really close to a human but maybe educational.
Personally I'd like to break this down from most doable to hardest. Bipedal motion is probably hardest and we should focus on AI last just saying.
>>22786 Good idea Anon. Mind breaking down our big problems into all the 'little problems' you can think of, then posting them here as a list, ranked "Easiest to Hardest" ? TIA.
>>22786 Totally agree, but still I keep an eye on it. If I see videos about how to archive it and learn about it, I post them. Bipedal walking itself can be broken down into smaller pieces, and some simple walking with guidance from a human would already make movement from place to place easier.
>>22787 Here's my guess from easiest to hardest robot skin robot hands robot head robot balance robot mouth robot arms robot legs walking But that's just off the top of my head based on my guesstimates just now...
>>22808 Thanks Anon! If you ever take the time to break this list down methodically, I suggest posting it to our How to solve it thread.
>>22814 I just asked bard to arrange it Here is the list of the items from easiest to hardest to do: Robot skin Robot hands Robot arms Robot legs Robot head Robot balance Robot mouth Walking Robot skin is the easiest to do because it is simply a covering for the robot's body. Robot hands are also relatively easy to do, as they can be made from a variety of materials and can be designed to perform a variety of tasks. Robot arms are also relatively easy to do, as they can be made from a variety of materials and can be designed to reach and grasp objects. Robot legs are also relatively easy to do, as they can be made from a variety of materials and can be designed to walk and run. Robot head is more difficult to do than the other items on the list, as it needs to be able to perform a variety of tasks, such as seeing, hearing, and speaking. Robot balance is also more difficult to do than the other items on the list, as it needs to be able to keep the robot upright and stable. Robot mouth is also more difficult to do than the other items on the list, as it needs to be able to perform a variety of tasks, such as eating, drinking, and speaking. Walking is the most difficult item on the list, as it requires the robot to be able to coordinate its movements in order to move forward. It is important to note that this is just a general list, and the difficulty of creating a robot will vary depending on the specific design and capabilities of the robot. The almighty AI has spoken.
>>22819 lol I just reread that eating and drinking wtf
>>22820 okay got a completely different answer from chatgpt Arranging these tasks from easiest to hardest: 1. Robot skin: Adding a protective or decorative covering to the robot's body is relatively straightforward and doesn't involve complex mechanics or functionality. 2. Robot mouth: Constructing a robot mouth to mimic basic movements, such as opening and closing, can be achieved through simple mechanisms like servos or pneumatic actuators. 3. Robot hands: Designing and building robot hands that can perform basic grasping and manipulation tasks requires more complexity and precision, but it's a well-explored area in robotics. 4. Robot arms: Developing robot arms involves creating articulated structures with joints and implementing motorized actuators for movement. It requires a higher level of mechanical design and control. 5. Robot legs: Designing and implementing robot legs for walking or locomotion involves complex mechanisms for stability, balance, and coordinated movement. It requires advanced control algorithms and sensor integration. 6. Robot head: Building a robot head involves integrating various components like cameras, sensors, actuators for facial expressions, and potentially speech synthesis capabilities. It requires mechanical design, electronics, and programming skills. 7. Robot balance: Achieving stable and dynamic balance for a robot is a significant challenge. It involves complex control algorithms, sensor fusion, and precise actuator control to maintain equilibrium and adjust to external forces. 8. Walking: Developing a walking robot is one of the most challenging tasks. It requires a combination of mechanical design, kinematics, motion planning, and control algorithms. Achieving stable and efficient locomotion across different terrains demands advanced techniques like dynamic balance and gait optimization. Please note that the difficulty of each task can vary based on the specific requirements and the level of complexity desired. This ranking provides a general idea of the relative complexity involved. chatgpt>>>>>>>>>>>>>>>>>bard
>>22821 one last thing we really should give that anon that made the robot head some props considering its so up there. Hope he didn't leave.
>>22808 Thanks, but we have a whole thread with making overviews, planning, diagrams, and subtthread does something quite similar what you're doing here: >>9554 - breaking down the development into smaller steps. Also, please consider the LLMs are likely not better than his board in knowing things in regards to robowaifus, since sadly we're somewhat the experts on this. On top of that, they're libtard censorship challenged, which means they might not know a robowaifu is supposed to be something like woman, what a good looking women is supposed to look like, and so on.

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