Rapidly Exploring Random Life
This talk will reflect on Professor Steven M. LaValle's life and career development as a University of Illinois alumnus. Anecdotes and lessons learned as a student, professor, entrepreneur, and industry leader will be interspersed with some of his technical work in the areas of robotics and virtual reality. The talk will conclude with some thoughts about where industry, research, and education in virtual and augmented reality are heading, or at least ought to be heading.
Bio: Steven M. LaValle is one of the preeminent figures in robotics research, not only revolutionizing motion planning, but also blazing new trails in minimal sensing and virtual reality (VR).
LaValle’s groundbreaking contribution to motion planning, a basic operation in almost all robotics, is the Rapidly-exploring Random Tree (RRT), which is included in top robotics libraries for use in autonomous vehicles, manufacturing, and humanoid robots. RRTs are also used for protein folding, drug design, automated video game characters, virtual prototyping, architecture, and digital acting.
LaValle has created novel solutions to common problems such as navigation, pursuit-evasion, target tracking, and surveillance, but with cheaper and simpler components than previously necessary. This work in minimal sensing was attractive to Oculus VR.
At Oculus VR, LaValle led the company’s research and development efforts. He holds a patent on perception-based tracking, crucial for reducing the Oculus Rift’s perceived tracking latency. A second patent covers sensor calibration and filtering methods, critical for accuracy and low-latency. Since returning to Illinois, he introduced CS498 "Virtual Reality," bringing his industry knowledge to the classroom.