[Apologies for multiple postings]
Robotic Motion Planning, Re-planning, and Parallelization
GRAND Seminar <http://cs.gmu.edu/~robotics/pmwiki.php/Main/GrandSeminar>
November 11, 12 noon, Room 4201
Michael Otte <http://www.mit.edu/~ottemw/>
Reliable sensors, open-source software, and the steady march of Moore’s law
have finally placed robotic technologies within the reach of the average
citizen. However, we are still searching for motion planning and
coordination algorithms that allow robots to move and interact with the
same speed, grace, and harmony as humans. My goal is to make the latter a
reality, and this talk will highlight some of my work on re-planning in
dynamic environments and parallelization of algorithms. In particular, I
will talk about RRT-X and C-FOREST.
RRT-X is a new Re-planning algorithm that allows real-time navigation in
environments that change unexpectedly. Theoretical results derived in the
creation of RRT-x lend insight into the two other popular algorithms RRT*
(Karaman and Frizzoli) and RRT# (Arslan and Tsiotras).
C-FOREST is a parallelization framework for sampling-based motion planning
algorithms that achieves significant super-linear speedup in practice (for
example, using 64 CPUs yields a speedup over 300X). It has recently been
included in the popular The Open Motion Planning Library (OMPL) maintained
by the Kavraki Lab at Rice University.
*About the Speaker*
Michael Otte is a Researcher at the University of Colorado at Boulder in
residence at the Aerospace Systems Directorate at the Air Force Research
Laboratory, prior to that he was a Postdoctoral Associate at the MIT
Laboratory for Information and Decision Systems. He received his PhD in
2011 from the University of Colorado at Boulder. He currently works on the
application of artificial intelligence to robotics, with a focus on path
planning and multi-agent systems.
George Mason University
MASC Group: http://masc.cs.gmu.edu