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<title>Siddhartha S. Srinivasa: University of Washington</title>
<meta name="Keywords" content="Siddhatha Srinivasa, Robotics, Seattle, University of Washington, Paul G. Allen School of Computer Science & Engineering" />
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<a href="index.html" style="font-size:40px;text-align:left;">Siddhartha S. Srinivasa</a><br/>
<div style="text-align:left"><a href="https://www.cs.washington.edu/people/faculty/siddh">Boeing Endowed Professor</a><br/>
<a href="https://www.cs.washington.edu/">Paul G. Allen School of Computer Science & Engineering</a> <a href="http://www.washington.edu/"><br/>University of Washington</a><br/><br/></div>
<div style="text-align:left"><a href="index.html">Home</a> |
<a href="research.html">Research</a> |
<a href="publications.html">Publications</a> |
<a href="cv.html">CV</a> |
<a href="contact.html">Contact</a> </div>
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I am currently focussing on two topics: <b>Physics-based Manipulation</b> and <b>The Mathematics of Human-Robot Interaction</b>. They are heavily intertwined, both born out of the goal of robots performing complex manipulation tasks with and around people.
<p><b>Physics-based Manipulation:</b>
I focus on using physics in the design of actions, algorithms, and hands for manipulation:
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<li>Manipulation is more than pick-and-place. We are developing <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=6652">nonprehensile physics-based actions</a> and algorithms to <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=7080">reconfigure clutter</a> in the way of the primary task by pulling, pushing, sweeping, and sliding it out of the way.
We have also recently shown that a class of tactile localization problems can be formulated to be <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=7264">submodular</a>.</li>
<li>I am particularly fond of functional gradient methods which have been used with much success in <a href="http://en.wikipedia.org/wiki/Path_integral_formulation">physics</a>.
We have developed <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=6285">CHOMP</a>, a functional gradient optimizer for robot motion planning, and variants like <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=6810">GSCHOMP</a> that exploit the structure of manipulation problems.</li>
<li>I believe simple hands can do complex things. I am working on building robustness into the design and algorithms of <a href="http://www.ri.cmu.edu/research_project_detail.html?type=description&project_id=661&menu_id=261">simple hands</a>, embracing physics and underactuation to stabilize objects.</li>
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<p><b>The Mathematics of Human-Robot Interaction:</b>
I focus on formalizing Human-Robot Interaction principles using machine learning, motion planning, and function gradient algorithms:
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<li>We have been working on enabling seamless and fluent human-robot handovers. We have developed a taxonomy of <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=6789">human and dog handovers</a>, designed expressive <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=6925">grasps</a> and <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=6793">motions</a>, and used time-series analysis to learn the <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=7258">communication of intent</a>. Our <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=7389">JHRI paper</a> summarizes this work.</li>
<li>We are <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=7077">formalizing assistive teleoperation</a>, framing it as the joint tightly-coupled problem of prediction, solved with machine learning, and arbitration by policy blending, solved with control theory. We are also working on the <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=7224">online adaptation of teleoperation interfaces</a> with kernel machines. </li>
<li>Our latest work formalizes <a href="http://www.ri.cmu.edu/publication_view.html?pub_id=7400">predictable and legible motion</a> as inference problems, bringing together concepts in psychology, animation, and machine learning. We are presently working on generating legible motion via functional gradient optimization.</li>
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I have greatly enjoyed collaborating with HRI researchers, and our joint exploration has broadened my understanding of humans, robots, and mathematics.</p>
<p> I am also interested in <b>Manipulation Planning</b>: <a href="http://personalrobotics.ri.cmu.edu/projects/cplan.php">extending randomized planners to constraint manifolds</a> and <b>Perception for Manipulation</b>: my group has developed <a href="http://personalrobotics.ri.cmu.edu/projects/moped.php">MOPED: an efficient object recognition and pose estimation system for manipulation</a>.</p>
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<p style="font-color:black;text-align:center">Siddhartha Srinvasa. All Rights Reserved. 2016.<br>
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