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X-APPLE-TRAVEL-ADVISORY-BEHAVIOR:AUTOMATIC
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 0250131T160000
URL;TYPE=URI:/news/calendar/events/rbe-c
 olloquium-speaker-connor-mccann
RBE Colloquium Speaker - Connor McCann
Enabling Mechanical Intelligence through Hybrid-Stiffness Robotics\n\n\n\n      \n      \n\n\n\nAbstract:
  In recent years, there has been growing recognition that the physical bod
 ies of animals play just as crucial a role in performing complex tasks as 
 the control signals that drive them. In the field of robotics, this has gi
 ven rise to the concept of 鈥渕echanical intelligence,鈥?whereby desired 
 behavior is embedded directly into robotic hardware rather than relying pu
 rely on active control. Though much work remains to match the level of per
 formance found in nature, great progress has been made by both soft and ri
 gid roboticists, alike. In this talk, Connor McCann will present his resea
 rch at the intersection of these two fields, showcasing strategies to embe
 d intelligent behavior into both rigid robotic hands and soft wearable reh
 abilitative robots using a combination of experimental, theoretical, and n
 umerical techniques. Looking toward future work, he will propose a new par
 adigm to achieve mechanical intelligence through 鈥渉ybrid-stiffness鈥?ro
 bots that combine soft and rigid components in tandem鈥攎uch like is found
  in nature鈥攖o leverage the benefits of each. In this way, he hopes to pu
 sh the bounds of what is possible with robotic hardware, seeking to imbue 
 it with the greatest degree of intelligence possible to achieve more rich 
 and complex robotic behavior than is currently feasible.\nBio: Connor McCa
 nn is a Ph.D. candidate in Mechanical Engineering at Harvard University, w
 here he has developed soft wearable robots for shoulder joint assistance, 
 creating new techniques for the experimental characterization, reduced-ord
 er modeling, and numerical simulation of these complex systems. He has als
 o studied the mechanics of stingray pectoral fins, seeking to understand h
 ow their intricate skeletal structures help to optimize their swimming eff
 iciency. Prior to working at Harvard, he completed his bachelor鈥檚 degree
  in Mechanical Engineering at Yale University, where he developed novel ro
 botic hands based on parallel mechanisms to improve within-hand dexterity.
 \n
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