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Full-Text Articles in Physical Sciences and Mathematics
Optimizing Tensegrity Gaits Using Bayesian Optimization, James Boggs
Optimizing Tensegrity Gaits Using Bayesian Optimization, James Boggs
Honors Theses
We design and implement a new, modular, more complex tensegrity robot featuring data collection and wireless communication and operation as well as necessary accompanying research infrastructure. We then utilize this new tensegrity to assess previous research on using Bayesian optimization to generate effective forward gaits for tensegrity robots. Ultimately, we affirm the conclusions of previous researchers, demonstrating that Bayesian optimization is statistically significantly (p < 0:05) more effective at discovering useful gaits than random search. We also identify several flaws in our new system and identify means of addressing them, paving the way for more effective future research.
A Better Way To Construct Tensegrities: Planar Embeddings Inform Tensegrity Assembly, Elizabeth Anne Ricci
A Better Way To Construct Tensegrities: Planar Embeddings Inform Tensegrity Assembly, Elizabeth Anne Ricci
Honors Theses
Although seemingly simple, tensegrity structures are complex in nature which makes them both ideal for use in robotics and difficult to construct. We work to develop a protocol for constructing tensegrities more easily. We consider attaching a tensegrity's springs to the appropriate locations on some planar arrangement of attached struts. Once all of the elements of the structure are connected, we release the struts and allow the tensegrity to find its equilibrium position. This will allow for more rapid tensegrity construction. We develop a black-box that given some tensegrity returns a flat-pack, or the information needed to perform this physical …