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Achieving Human Level Competitive Robot Table Tennis
- aaron695 1y ago[dead]
- BugsJustFindMe 1y ago> that reaches amateur human-level performance in competitive table tennis How are we defining amateur here? The presented video shows the human intentionally volleying with the robot, barely putting any force at all behind the returns. But it says the robot won 55% of matches against intermediate players? That requires being able to return much harder shots than shown.
- push0ret 1y agoThey note that the robot achieved an "intermediate" skill level. This has been determined by letting it play matches against people of different skill levels as determined by a professional table tennis coach. The "Results" section explains this.
- BugsJustFindMe 1y agoBut they don't explain what metrics they use to differentiate skill level other than waving the hands of a puppet coach. The arm control is great but they don't show it returning non-softballs. Is that what "intermediate" means?
- spongebobstoes 1y agoProbably, if you consider that a beginner can rarely volley at all. At an intermediate level, a fast return pretty much just wins the point, when it doesn't hit the net or miss the table.
- repeekad 1y agoGoogle had a very competitive employee ping pong league and one of the coaches was on the USA Olympic team, I doubt they would lie about ping pong skills
- hooloovoo_zoo 1y agoIt looks very slow in the videos though.
- eviks 1y agoWhat do you think the mechanism is that would make them honest?
- repeekad 1y agoGooglers are well known for speaking up when they disagree with something the company is doing, but yeah I mostly wanted to call out how big the ping pong culture is at Google at least in Mountain View
- yusina 1y agoJust watch the videos. They don't support your statements.
- croemer 1y agoSubmitted on 7 Aug 2024 https://arxiv.org/abs/2408.03906 https://arxiv.org/abs/2408.03906
- huem0n 1y ago> Policy performance was assessed through 29 robot vs. human matches of which the robot won 45% (13/29)
- socalgal2 1y agoUntil the robot is standing on its own two legs like a human I feel like it doesn't count. Sliding along a rail isn't comparible
- falcor84 1y agoIt counts a lot for me. There's enough examples of humans playing table tennis; I'm very intrigued about how the same problem can be solved by alternate means.
- programjames 1y agoPeople did the conveyor belt thing in the 60s.
- thedevilslawyer 1y agoCitation?
- programjames 1y agoI can only find papers from the late 1980s on this, but a professor around during the 60s told me hackers were working on robotic ping-pongers way back then.
- Chipen 1y agoDoes the ball hit by the robot have spin, or is it just a normal return? I'm kind of curious.
- kerkeslager 1y agoBased on what I'm seeing in the video, the robot isn't slicing the paddle in a way that would impart much spin other than what's already there. This is essentially a defensive play style. That's not to say that the ball doesn't have spin. I play with a lot of spin, and a recent level up in my game was that I realized that when I put spin on the ball and my opponent returns it without slicing, I've got to account for the spin I put on it because it's still there. You can get pretty dang far with a primarily defensive style, though. I was recently at an informal local tournament where the 2nd place guy had basically one serve and an insane ability to return shots. A lot of the times he scored in the final game were where his opponent hit a shot with such insane speed and spin that when when he returned it, his opponent couldn't defend the residual speed/spin of his own shot.
- YeGoblynQueenne 1y agoSmart :)
- programjames 1y agoFeels like clickbait. People were doing similar things in the 60s at MIT. I thought by "human level robot" they meant actually human level, with a humanoid robot swinging the paddle, not a conveyor belt.
- mitthrowaway2 1y agoI'm pretty sure Omron has been bringing a table tennis robot to trade shows for at least ten years, and it's pretty good at the game. They mention it in their paper: > A key point of difference is that our agent learns the control policies and perception system, whereas the Forpheus agent uses a model-based approach. More specifically, Forpheus leverages rebound and aerodynamics models in order to identify the optimal configuration of the robot so as to return the ball to a target position. The Omron system represents a highly engineered system that cannot easily be customized to new players, environments, or paddles But I think they're stretching a bit to claim that a model-based design can't be easily customized. Many of us would consider it much easier to plug in a new air viscosity or coefficient of restitution value into a model than to re-train a physical robot.
- red75prime 1y ago> than to re-train a physical robot Where we are going the robot retrains itself.
- nikolayasdf123 1y agointeresting, I would expected this problem to be much simpler than it turns out
- yusina 1y agoIt is. It's just that we now live in an age where everything has to be solved with "AI" to get attention and justify the billions of investments. So we forget established tech and enter the era of AI enshittification where this kind of thing is considered an amazing achievement. Had this been some high school kids I'd be impressed. But Google? C'mon.
- huem0n 1y agoI don't find this particularly impressive for DeepMind, mostly because it seems like a ballistics/physics problem rather than a machine learning problem. Edit: yep here's a better performing robot from 6 years ago based on ballistics: https://m.youtube.com/watch?v=u3L8vGMDYD8&pp=0gcJCYQJAYcqIYzv https://m.youtube.com/watch?v=u3L8vGMDYD8&pp=0gcJCYQJAYcqIYz... If DeepMind wanted to emphasize the learning aspect of it (and they should) then it should be in the title. E.g. "Novel learning algorithm leads to competitive robotic table tennis"
- smegma2 1y agoThe paper addresses this. Part of the goal was to let the world model be learned rather than modeled explicitly by the programmer. > To date, the Omron Forpheus robot [73], [62] has the closest capabilities to the agent presented in this work, demonstrating sustained rallies on a variety of stroke styles with skilled human players. A key point of difference is that our agent learns the control policies and perception system, whereas the Forpheus agent uses a model-based approach. More specifically, Forpheus leverages rebound and aerodynamics models in order to identify the optimal configuration of the robot so as to return the ball to a target position. The Omron system represents a highly engineered system that cannot easily be customized to new players, environments, or paddles. > While there have been many demonstrations of robots playing table tennis against human players in the past, we believe this research is one of the first human-robot interaction studies to be conducted with full competitive matches against such a wide range of player skill levels.
- almosthere 1y agoWhat in the world is this huge push to have robots? Are people not good enough?
- npteljes 1y agoI think on a population / humanity level, there is no such thing as "good enough". There is always something new to experiment with, something to improve, something to change. This bother seems to propel humans since time immemorial.
- artofpongfu 1y agoVery cool, but "Our approach lead to competitive play at human level and a robot agent that humans actually enjoy playing with": I would not call that remotely near "human level" yet. I think we'll get there at some point but I think people underestimate how difficult table tennis is and the level of top human play is insane. This was the World Cup match point recently for reference: https://www.youtube.com/shorts/-AJg2u7U5MU https://www.youtube.com/shorts/-AJg2u7U5MU As a little side project I'm working on a table tennis AI for VR which works by imitating real players, which is a much simpler problem since you're allowed to "fake" a lot of things in a game. I think VR holds more promise in the short to medium term for practicing TT than robotics.
- hyperbrainer 1y agoMost table tennis players don't play at the level of the World Cup.
- artofpongfu 1y agoYeah, but I don't think anyone who's played TT regularly would call this "intermediate". It's like calling someone who managed to code fizzbuzz an intermediate programmer.
- yusina 1y agoExactly this. A world-class player could beat this thing left-handed with one eye closed.
- artofpongfu 1y agoLeft-handed, one one leg, one eye closed and a mobile phone instead of a racket. Reminds me of a clip of Truls Moregardh playing a reporter with a phone: https://www.youtube.com/watch?v=3EJaT1b8QmA https://www.youtube.com/watch?v=3EJaT1b8QmA
- kerkeslager 1y agoTo be honest this feels a bit pedantic to me. "Intermediate" is a pretty vague word and unless there's some official rankings termed "intermediate" I'm unaware of, the authors of this paper are fine to apply it as they see fit. There are a significant number of players worse than the robot, and a significant number of players better. That's fact, and that's all "intermediate" means.
- endofreach 1y agoI don't wanna brag, but i remember building something similar when i was 6 or years old... by folding up one side of the table.
- deleted 1y ago[deleted]
- perlgeek 1y agoAs somewhat of a table tennis nerd, I really like this, but also cannot help to throw in some critical observations :-) I've skimmed through the match highlights video, and it struck me that there wasn't really any engagement with spin. You can hear from the relatively high pitch of the ball contact that these were rubbers with very thin sponges or no sponge at all, and likely not enough grip to cause any real rotation on the ball. Even in the lowest leagues (here in Germany, at least), people use backspin to prevent attacks, and varying the spin is half the game. Also, human players often have different rubbers on the forehand and backhand sides, which is why rules demand that both rubbers have very distinct colors. Using black rubbers on both sides kinda demonstrates their non-engagement with spin. That said, kudos for making a robot that people enjoy playing with. That's not a given. Players anticipate the trajectory of the ball based on the opponent's body movement, which a robot could totally subvert. Physical limitations also play a real role in table tennis, for example the forehand flick is much harder to play than the backhand flick due to the way our hand joint works. A robot wouldn't be subjected this particular limitation.
- breakyerself 1y agoI'd be more impressed if this was in a humanoid robot.
- mathgradthrow 1y agoit's a little disingenuous to claim human level performance at a sport when you use a robot arm on a track. Humans have to contend with a body not specifically suited to the problem.
- YeGoblynQueenne 1y agoThe interesting result here is not the performance against human players, which DeepMind tries to upsell. The interesting bit is their approach to bridging the sim-2-real gap by iteratively training in a simulation and fine-tuning in real-world games. The approach is described here: i-Sim2Real: Reinforcement Learning of Robotic Policies in Tight Human-Robot Interaction Loops https://sites.google.com/view/is2r https://sites.google.com/view/is2r The sim-2-real gap is a real obstacle in adopting RL for rotobics and anything that pushes the envelope is worth the trouble. On the other hand, I can't tell how well this approach will work outside of Table Tennis. Note that on top of the RL work there is, AFAICT a metric shit ton of good, old-fashioned engineering to support the decision-making ability of learned policies. E.g. the "High Level Controller" (HLC) that selects "Low Level Controllers" (LLC) using good, old-fashioned AI tools, tree search with heuristics, seems to me to be hand-crafted rather than learned, and involves a load of expert knowledge driving information gathering. So far, no bitter lessons to taste here. Oh and of course the HLC is a symbolic component while the LLCs are learned by a neural net. Once more DeepMind sneakily introduces a neuro-symbolic approach but keeps quiet about it. They've done that since the days of AlphaGo. No idea why they're so ashamed of it, since it really looks like it's working very well for them.
- bilsbie 1y agoHow far are we from pickleball? I’d pay big money for a pickleball robot.