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SUMMARY:GRASP Seminar: Lillian Chin\, University of Texas at Austin\, "Materials Make the Bot: Directly Embedding Actuation and Perception into Robotic Structures"
DESCRIPTION:*This seminar will be held in-person in Levine 307 as well as virtually via Zoom.  \nABSTRACT\n\nTo make a future where robots are helpful and commonplace\, robots must physically interact with humans and their surroundings. In this talk\, I argue that robots should be designed from a materials-centric approach to better facilitate these interactions. If core robotic features like actuation and perception can be directly incorporated into a robot’s materials\, we could directly control the robot’s primary interface to the outside world. \nDrawing from principles in mathematics and metamaterial design\, I use auxetic materials as a case study to show how metamaterials can be explicitly designed as the foundation for a robot’s movement and sensing capabilities. I demonstrate the power of this approach by creating expanding modular robots with strength-to-weight ratios of 76x and developing a novel class of auxetics that make soft robotic grippers that are 20x more efficient than standard pneumatic versions. I also present a method for directly sensorizing metamaterial structures in general by embedding internal fluidic channels within the struts themselves as the structure is being 3D printed. This technique offers proprioceptive feedback with minimal hysteresis\, enabling accurate pose reconstruction from these fluidic sensors alone. I close my talk with some preliminary work on adapting this materials-focused approach towards medical applications.
URL:https://seasevents.nmsdev7.com/event/grasp-seminar-lillian-chin-university-of-texas-at-austin-materials-make-the-bot-directly-embedding-actuation-and-perception-into-robotic-structures/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
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