204 citations · 495 across the 31 of their papers we have counts for
5 papers · 1 filter
Scalable sim-to-real transfer of soft robot designs
Sam Kriegman, Amir Mohammadi Nasab, Dylan Shah +5
The manual design of soft robots and their controllers is notoriously challenging, but it could be augmented---or, in some cases, entirely replaced---by automated design tools. Mac…
Sim2real gap is non-monotonic with robot complexity for morphology-in-the-loop flapping wing design
Kent Rosser, Jia Kok, Javaan Chahl +1
Morphology of a robot design is important to its ability to achieve a stated goal and therefore applying machine learning approaches that incorporate morphology in the design space…
Embodiment dictates learnability in neural controllers
Joshua Powers, Ryan Grindle, Sam Kriegman +3
Catastrophic forgetting continues to severely restrict the learnability of controllers suitable for multiple task environments. Efforts to combat catastrophic forgetting reported i…
Word2vec to behavior: morphology facilitates the grounding of language in machines
David Matthews, Sam Kriegman, Collin Cappelle +1
Enabling machines to respond appropriately to natural language commands could greatly expand the number of people to whom they could be of service. Recently, advances in neural net…
Automated shapeshifting for function recovery in damaged robots
Sam Kriegman, Stephanie Walker, Dylan Shah +3
A robot's mechanical parts routinely wear out from normal functioning and can be lost to injury. For autonomous robots operating in isolated or hostile environments, repair from a…