Math alum giving talk on robotics applications
Monday, October 30, 2006
Friday, Nov. 3, at 4 p.m. in Fenton Hall Room 105, Fredonia graduate Erion Plaku (computer science, 2000) will return to campus from his studies at Rice University to discuss motion planning and how it applies to robotics. The lecture is open to the public.
“Motion planning is in general necessary in order for robotic systems to carry out assigned tasks and objectives, such as exploration of unknown environments, autonomous or assisted driving, search-and-rescue operations, and many others,” Professor Ziya Arnavut (computer science) said.
The title of Mr. Plaku’s talk is “Effective Computational Methods for High-dimensional Motion Planning.” It is sponsored by the Math and Computer Science Scholarship program, which is funded at Fredonia by the National Science Foundation.
Mr. Plaku is a Ph.D. candidate in computer science at Rice University where he is studying algorithmic robotics under Prof. Lydia E. Kavraki. His research interests include high-dimensional motion planning for continuous and hybrid systems, large scale distribution of motion planning algorithms, proximity algorithms, and dimensionality reduction. After graduating from Fredonia in 2000, he earned his master’s degree in Computer Science from Clarkson University.
His talk will focus on methods developed during his research that have effectively solved motion planning problems with hundreds of dimensions, which previously could not have been dealt with in a practical amount of time. In many cases, the computational cost has been reduced by several orders of magnitude.
“The motion planning problem consists of finding a trajectory for a given system from an initial state to a goal state such that certain conditions are satisfied at each state of the trajectory,” Mr. Plaku said. “As an example, motion planning for a car requires the computation of a trajectory that not only connects the starting and destination places but also avoids collision and respects legal speed limits. Theoretical results provide strong evidence that the motion planning problem especially for high-dimensional robotic systems is computationally challenging.”
Share on Facebook
Previous Page | Next Page