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GRASP Special Seminar: Konstantinos Karydis, University of Delaware, “A Data-Driven Hierarchical Framework for Planning, Navigation, and Control of Uncertain Mobile Robots: With Applications to Miniature Legged Robots”

May 6, 2015 @ 1:30 pm - 2:30 pm


 Achieving navigation with state-of-the-art mobile robots in real-world settings is hindered because of the presence of uncertainty. Dealing with uncertainty in robot navigation is a difficult problem because it invalidates the performance guarantees available for deterministic settings, while its precise effect on motion cannot be predicted. Typically, we find uncertainty embedded within the system (“process uncertainty”), in perception, and in the environment. This talk focuses on tools for dealing with process uncertainty. The developed tools lay the basis for a general framework that can be used to quantify the effect of process uncertainty on robot motion, and still recover some performance guarantees for achieving motion tasks. If we could capture the variability in motion caused by process uncertainty, quantify risk, and establish performance trade-offs in its presence, we could then create consistent links between high-level objectives and low-level implementation. Such links would allow for robot navigation in real-world settings with performance certificates, a need that becomes pressing as robotics in consumer applications are rapidly gaining momentum. Dealing with uncertainty is not only important in robotics but also in general cyber-physical systems, and animal locomotion in small scales; elements of this work may find applications in these domains as well.

The main ideas of the approach are fixed using a particular application area: miniature legged robots. Reduction in scale magnifies the effect of uncertainty, and thus miniature legged robots provide a suitable testbed for the proposed framework; indeed, uncertainty enters naturally (e.g., inherent uncertain leg-ground interactions), while its effect on robot motion is clearly visible. By applying the framework to this area, real-time robot navigation and control at the miniature scale is enabled. The latter pushes the limits on what palm-sized crawling robots can achieve, and aids in shaping their potential in applications including building/pipe inspection, search-and-rescue, and wildlife monitoring.


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Konstantinos Karydis received with honors his Eng. Diploma in Mechanical Engineering from the National Technical University of Athens, Greece, in 2010. He is currently a PhD Candidate in the Department of Mechanical Engineering at the University of Delaware and expects to graduate in Summer 2015. His research interests include modeling and control of stochastic systems, uncertainty quantification and probabilistic model validation, as well as motion planning, navigation, and control of miniature legged robots.

Mr. Karydis is the recipient of the 2010 Helwig Fellowship offered by the Department of Mechanical Engineering at the University of Delaware, and the 2008 Greek State Scholarships Foundation (IKY) and Thomaideion Awards. Since 2014, he serves as a review editor for Frontiers in Robotics and AI, section Multi-Robot Systems.


May 6, 2015
1:30 pm - 2:30 pm
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