Happy New Year!
I would like to take this opportunity to highlight the tensegrity robotics related work by some of our many inspired collaborators. First of all, I’m excited to introduce Dr. Julian Rimoli of Georgia Tech, who has developed some excellent new tools for analyzing the structural response of a tensegrity robot when it lands on another planet. The resulting video of its dynamics is excellent.
This is what Julian has to say about his work:
“Most approaches to modeling tensegrity structures assume their bars are rigid, and that they only experience pure axial loads. In addition, a common design constraint is assuming that the structure would fail if any of its members buckle. The first two assumptions break down under highly dynamic events such as impacts, and the third one is not necessarily true: slender bars can sustain a load after failure, and consequently stresses would redistribute without necessarily producing structural failure. This video shows an example of a light-weight tensegrity structure under a highly dynamic event. The model accounts for the body forces and associated bending on bars, and their buckling and post-buckling behavior. The ground is modeled as elastic with friction. For those interested, details of the model will be presented at SciTech in January 2016.”
Next, Julian made a great video from the perspective of a camera mounted at a centrally suspended payload during the same landing event as the video above. This shows what the point of view might be for navigation purposes if you gimbaled the camera to stay stable while the robot bounced and rolled. This is a 360 degree video, so you can use the arrows to change the direction that you are looking out from the robot.
Finally, another video of his shows how waves of landing forces might propagate in an interesting manner through the tensegrity robot, making it appear to “inch-worm” its way back up into the air. Once again, this shows how unique and surprising these structures can be!
Next I would like to share the work of a team led by Will Buchanan who built an amazing tensegrity art structure and took it out to the Burning Man festival, where folks could climb and play on it.
Two members of our lab were part of the effort — Ken Caluwaerts and Atil Iscen, both of whom have contributed to the design and control of our SUPERball robot here at NASA. Best of all, Will and his team captured all the details and lessons learned from creating this giant tensegrity sculpture into an Instructable. Now you can go make your own giant tensegrity sculpture and have your friends play on it!
Finally, I would like to highlight some recent work by Ryan Adams, who has been an amazing contributor to the development of our open source physics based tensegrity robotics simulator (NTRT — the NASA Tensegrity Robotics Toolkit). Inspired by our use of coupled oscillators in the controls of tensegrity robots, he has been exploring the dynamics of fields of coupled oscillators. What is fascinating is how stable dynamic patterns readily emerge out of a randomly seeded field. This is not just the simple case of all the oscillators synchronizing with each other, but rather the emergence of stable repeating complex patterns, as shown in the video below.
OSim Demo #1 (64×64 grid, 2d) from Ryan Adams on Vimeo.
I think that this is a very important line of research for the understanding of neuroscience and the fundamentals of how we control motion — where a coordinated set of actions must be generated by a very noisy and error prone computational system (our neurons). This ability to start with a random set of oscillators, and have it settle into a stable behavior is exactly what would enable the robust and reliable behavior of animals despite the noisy reality of our neurons. This is obviously just an early stage exploration of the key principles, and a long way from a full theory of neuroscience, but it is valuable to see the key properties at play.
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