•   When: Tuesday, January 31, 2017 03:00 PM
•   Speakers: Lydia Tapia, Assistant Professor, Dept. of Computer Science, University of New Mexico
•   Location: ENGR 4201
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Mankind is on the cusp of a robotics revolution. Soon, cars will drive themselves and our packages will be autonomously delivered by flying robot. Despite these advances, there is one aspect of navigation that robots are currently unable to handle well: uncertainty. Navigation uncertainty comes from many sources, both internal to the robot, e.g, control or localization uncertainty, or external to the robot, e.g., changes in or uncertainty of the world around the robot. In this talk, we will address multiple forms of uncertainty that impact autonomous navigation. First, we consider navigation in environments that are changing stochastically. Our methods are the first to directly integrate stochastic changes that occur during navigation and provide real-time capable solutions for navigation. Next, we consider transition uncertainty that occurs when an action is taken but the outcome is unexpected. Through adaptation of learned plans, we demonstrate adjustment to certain forms of transition uncertainty. Finally, we consider model uncertainty, a lack of precision or error in the world model used to navigate. While this form of uncertainty often causes unintended collisions, we demonstrate how to quantify and adjust to predicted collisions.

Application of our methods spans both robotics and biological domains. In the robotics domain, we will demonstrate our solutions on autonomous vehicle navigation, aerial vehicles, and manipulation. In the biological domain, we investigate the impact of uncertainty in the simulation of antibody assembly, where multiple molecules are moving and interacting on a cell membrane.

Short Bio

Lydia Tapia is an Assistant Professor in the Department of Computer Science at the University of New Mexico. Since becoming an Assistant Professor, she has graduated two Ph.D. students (both with distinction, one earned the Popejoy Award for top dissertation at UNM), earned over 5 million in research and equipment funding (including a NSF CAREER Award and PI of a NSF National Robotics Initiative Grant), and filed two patents, one on a novel Unmanned Aerial Vehicle design and another on a method to design an allergy treatment. She achieves this amazing work due to her thriving research team, the Adaptive Motion Planning Research Group, that simulates and analyzes the motions involved in both molecular and robotics applications. Her students have won an international award for undergraduate research, a national conference research award, and regional awards for high school computing. When they are not in the lab, you can often finding them doing interactive robot demos for the community at local schools, robotics competitions, and previously at the New Mexico State Fair.