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SUMMARY:Computational Design & Fabrication of Robots
DTSTART:20200211T124500
DTEND:20200211T134500
DTSTAMP:20260510T001448Z
UID:53bc6610f54ab4ef2f9113fc72bf9c83441828ee49e696d1c56c5fb5
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Josie Hughes\, Distributed Robotics Lab\, MIT\nAbstract:\n
 Automating the design and creation of complex robots is challenging due to
  the complexity of the design search space and physical processes required
 .  To address this\, data-driven approaches are required to understand ho
 w to design and optimize robotic structures for a given task.  This talk 
 introduces a number of techniques and processes for the computational desi
 gn of robots\, focusing on automated design\, rapid fabrication\, and task
 -specific learning.  This includes approaches ranging from biologically i
 nspired design\, to developing terrain optimized robots by searching over 
 10\,000s of possible designs\, and Bayesian based approaches for rapid tas
 k learning.  Different application scenarios for these approaches are als
 o presented.  The talk concludes with a vision for the future in which be
 spoke robots can be automatically created for a given task.\n\nBio:\nJosie
  Hughes completed her Undergraduate\, Masters and PhD at the University of
  Cambridge.  She completed her PhD in 2018\, developing robots which util
 ize embodied mechanics and sensory coordination for advanced capabilities.
   Her research focused on manipulation\, sensor technologies and new appr
 oaches for designing and fabricating complex anthropomorphic manipulators.
   Josie is now working as a Post-Doctoral Research Associate in the Distr
 ibuted Robotics Lab\, MIT.   At MIT she is working on computational desi
 gn methods\, wearable technologies and new novel robot fabrication methods
 .  Her work has been published in Science Robotics\, Nature Machine Intel
 ligence\, Soft Robotics and many other conferences and journals.  Additio
 nally\, she has lead teams which have won over 5 International Robotics Co
 mpetitions.
LOCATION:BM 5202 https://plan.epfl.ch/?room==BM%205202
STATUS:CONFIRMED
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