On October 2, the University of Kentucky Department of Computer Science will welcome Dinesh Manocha, Phi Delta Theta/Mason Distinguished Professor of Computer Science at the University of North Carolina at Chapel Hill, as the speaker for a colloquium at the Davis Marksbury Building. The event will begin at 4:00 p.m.
Dr. Manocha has co-authored than 330 papers in the leading conferences and journals on computer graphics, robotics and scientific computing. He has also served as program chair for many conferences and on the editorial boards of several leading journals. Dr. Manocha has received distinguished awards, among them the Alfred P. Sloan Fellowship, a NSF Career Award, the Office of Naval Research Young Investigator Award and 12 best paper awards at leading conferences. He is a Fellow of ACM, AAAS and IEEE and received a Distinguished Alumni Award from the Indian Institute of Technology in Delhi.
Here is an excerpt from the abstract describing the subject of Dr. Manocha’s talk.
“From record-setting crowds at rallies and protests to futuristic swarms of robots, our world is currently experiencing a continuing rise of complex, distributed collections of independently acting entities. With potential applications such as computer graphics, predicting crowd disasters, improving robot cooperation and enabling the next generation of air travel, developing models to reproduce, control, predict and understand these types of systems is becoming critically important.
In this talk, I will give an overview of how to use velocity-space planning techniques to compute cooperative motion paths for a group of independent entities sharing the same physical space. I will focus on the special case of simulating human-like crowds, with applications to computer animation and architectural analysis. Specific topics will include optimization-based strategies for distributed collision avoidance, uses of the principle of least effort for simulating crowds and data-driven strategies for modeling differences in personalities. The talk will also cover related techniques needed to achieve accurate simulations of large-scale crowds such as efficient parallel/SIMD compute models and methods of validating simulations against real world data and will discuss how velocity-space motion planning can be applied to collision avoidance for distributed robotic systems.”