4 ms·
I saw Vytas' presentation at the NIAC symposium a few weeks ago, and as someone whose only previous exposure to tensegrity systems was the typical outsider's vi
by FiatLuxDave 12y ago
I saw Vytas' presentation at the NIAC symposium a few weeks ago, and as someone whose only previous exposure to tensegrity systems was the typical outsider's view of its use in architecture and toys, I have to say that his robots are damn cool. I'll post a link to the video after I get out of the meeting I have in a few minutes, if no one beats me to it. If you haven't seen this stuff it's worth seeing just for the cool factor alone.
I agree with you that one of the most difficult things about tensegrity structures is predicting their behaviour under stress and failure - and since behaviour under exactly those circumstances is also one of the main strengths of the concept, that kinda sucks. It's like trying to sell a car which gets better gas mileage, but you can't really predict how much. Better but unpredictably better can be a hard sell and especially bad when trying to optimize a plan for.
I see a lot of parallels between the concept of tensegrity and certain concepts of resilient design of complex software. In both cases, testing (and having good test cases) is a vital component of testing. In both cases, even with testing it is hard to have a good predictive model of failure, because at a certain level the complexity of test cases can start to compete with the design itself.
What I see as the really cool thing about what Vytas is doing, is the addition of controls (e.g. motors etc) to tensegrity structures. This only adds to the complexity when it comes to testing, because now there are many more variables. However, if this is a huge issue, it is theoretically possible to set the controls in such a way that it actually reduces the space of possible behaviours, and thus makes analysis more tractable. Of course, I think it's much cooler to go the other way and make the darn things do crazy stuff, but it all depends upon what you need out of a design. It's somewhat the same issue with a robotic arm: it can move in so many ways, sometimes the easy or safest way to do a job is to restrict the possibilities (like not letting it move into a danger zone). But making it dance is more fun!
- akagogino 12y agoI'm working with Vytas at NASA on the control issues for these tensegrity robots. One of our main ways to address the complexity issue is to use machine learning to determine control parameters. We have been using traditional evolutionary techniques as well as some techniques related to importance sampling. A counterintuitive result of using evolutionary controls is that the control problem does not necessarily become more difficult as the complexity of the structure increases. This is because the number of good solutions may increase faster than the solution space. Currently in hardware, we are building relatively simple structures, but we hope to expand to more complex ones in the future.
- TheLoneWolfling 12y agoSo effectively, the percentage of good solutions increases as the complexity increases?
- FiatLuxDave 12y agoLink to the Super Ball Bot video from the NIAC conference: http://new.livestream.com/viewnow/NIAC2015/videos/75238510 http://new.livestream.com/viewnow/NIAC2015/videos/75238510 at 33:03 into the video.