•   When: Thursday, October 05, 2017 from 11:00 AM to 12:00 PM
•   Speakers: Erion Plaku
•   Location: ENGR 4201
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As robots are deployed into less and less structured environments, it becomes increasingly important to enhance their ability to complete high-level tasks with little or no human intervention. Whether the task is to search, inspect, or navigate to target destinations, it generally involves decomposing it into discrete, logical actions, where each discrete action often requires complex collision-free and dynamically-feasible motions in order to be implemented. This talk will discuss our research efforts on a computationally-efficient framework and a formal treatment of the combined task and motion- planning problem as search over a hybrid space consisting of discrete and continuous components. The framework makes it possible to specify high-level tasks via Finite State Machines, Linear Temporal Logic, and Planning-Domain Definition Languages and automatically computes collision-free and dynamically-feasible motions that enable the robot to accomplish the assigned task. Applications in autonomous underwater vehicles will be highlighted.

Erion Plaku is an Associate Professor in the Department of Electrical Engineering and Computer Science at Catholic University of America. He received his Ph.D. degree in Computer Science from Rice University in 2008. He was a Postdoctoral Fellow in the Laboratory for Computational Sensing and Robotics at Johns Hopkins University from 2008 to 2010. Plaku's research is in Robotics and Artificial Intelligence, focusing on enhancing automation in human-machine cooperative tasks in complex domains, such as mobile robotics, autonomous underwater vehicles, and hybrid systems. His research is supported by NSF Intelligent Information Systems, NSF Software Infrastructure, and the U.S. Naval Research Laboratory. More information, including publications, research projects, open-source software he has developed for robot motion planning, and educational materials can be found at http://robotmotionplanning.org