The Robotics Institute, Carnegie
Mellon University · 5000 Forbes Ave, Pittsburgh, PA
15213 bargall@ri.cmu.edu · 412. 268. 9923 |
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This page is no longer being updated. As of May 2009, I am affililiated with EPFL as a postdoc within the Learning Algorithms and Systems Laboratory (LASA). Please visit my current website here.![]() My research interests lie with robot autonomy and low level motion control, and how machine learning may be used to build control algorithms to accomplish motion tasks. I am affiliated with the CORAL Research Group. My resume may be found here. For part of 2007 I lived in Doha, Qatar, while assistant-teaching at Carnegie Mellon's Qatar Campus. In the summer of 2008 I was an intern within the Autonomous Systems Laboratory at CSIRO in Brisbane, Australia. I also volunteer as a procedure counselor with Planned Parenthood. |
My research
interests center upon using machine learning techniques that build
low level robot motion control algorithms, also called policies. The execution of
motion tasks is central to the success of many
robotics applications. However, developing policies which enable
skillful execution within real world environments is often
challenging and nontrivial. One solution is to have a robot learn its
policy. I focus on the particular approach of Learning from
Demonstration. Within this
learning paradigm, a teacher
demonstrates to provide example executions of a task, and from these
the learner generalizes a control policy.
Projects Brain
Imaging with fMRI |
B. Argall, B. Browning, and M. Veloso.
Learning
Robot
Motion Control from Demonstration and Human Advice. Under submission.
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B. Argall, B. Browning, and M. Veloso.
Automatic
Weight Learning for Multiple Data Sources when Learning from
Demonstration. To appear, in Proceedings IEEE International Conference on Robotics
and Automation (ICRA 2009),
Kobe, Japan, May 2009. (pdf)
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