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  <title><![CDATA[Smoothing contact-rich dynamics using morphological computation]]></title>
  <body><![CDATA[<h3><strong>Soft Condensed Matter &amp; Physics of Living Systems Seminar: Prof. Sam A Burden, University of Washington</strong></h3>

<p>&nbsp;To move over, around, or through obstacles in the world, robots and animals need to employ a repertoire of dynamic and dexterous behaviors.&nbsp; Since the world is ever-changing, these behaviors must be synthesized on-the-fly and adapted to diverse environmental conditions.&nbsp; At present, animals deftly outperform autonomous robots in this regard.&nbsp; We seek tools that will enable the performance of dynamic legged robots to surpass that of their animal counterparts.</p>

<p>In this talk, we discuss advances in modeling and control of dynamic legged locomotion.&nbsp; Unlike some areas of robotics and biomechanics, models for most dynamic legged behaviors have poor predictive power.&nbsp; In particular, rigid-body models of legged locomotion yield predictions that vary discontinuously when multiple limbs contact terrain.&nbsp; By introducing compliance in hips and feet, we show that model predictions vary smoothly with respect to initial conditions (including states, parameters, and inputs).&nbsp;</p>

<p>Smooth model predictions are amenable to scalable algorithms for estimation, optimization, and learning; we briefly discuss our current efforts and future plans in these directions.&nbsp; We conclude that compliance in hips and feet perform morphological computations that can simplify modeling and control of dynamic legged locomotion.</p>

<p><strong>BIOGRAPHY</strong></p>

<p>Sam Burden earned his BS with Honors in Electrical Engineering from the University of Washington in Seattle in 2008.&nbsp; He earned his PhD in Electrical Engineering and Computer Sciences from the University of California in Berkeley in 2014, where he subsequently spent one year as a Postdoctoral Scholar.&nbsp; In 2015, he returned to UW EE as an Assistant Professor; in 2016, he received a Young Investigator award from the Army Research Office (ARO-YIP).&nbsp; Sam is broadly interested in discovering and formalizing principles of sensorimotor control.&nbsp; Specifically, he focuses on applications in dynamic and dexterous robotics, neuromechanical motor control, and human-cyber-physical systems.&nbsp; In his spare time, he teaches robotics to students of all ages in classrooms and campus events.</p>
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      <value><![CDATA[<p>shaun.ashley@physics.gatech.edu</p>
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