Title: Unified Autonomy across Robot Configurations
(https://www.csd.uoc.gr/CSD/index.jsp?content=news&ann=759)
Speaker: Prof. Dr. Kostas Alexis,
Head of the Autonomous Robots Lab, Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU),
Director of the Norwegian Centre for Embodied AI
Location: K206, Computer Science Department, University of Crete
Date: Tuesday, October 27, 2026
Time: 11:00
zoom: https://uoc-gr.zoom.us/j/83264009430
Host: Prof. Panos Trahanias
Abstract:
State-of-the-art autonomy methods remain fragmented with controllers, sensor fusion pipelines, and learning algorithms typically tailored to narrow robot morphologies and operating regimes. This specialization has historically been necessary to achieve operational results, but inevitably limits generalization and slows the pace of innovation. A common blueprint for autonomy is necessary. This talk outlines results toward resilient Unified Autonomy that is applicable across diverse robot embodiments, whether flying, aquatic, or ground systems. By pursuing a shared but morphologically-conditioned autonomy architecture and leveraging the lessons learned from its broad evaluation in extreme conditions, we demonstrate resilient functionality that transfers across robot morphologies. The discussion will highlight both the underlying methods that enable this unification as well as concrete results from field testing in unconventional environments - such as subterranean settings, ship ballast tanks, and submarine bunkers.
Bio: Prof. Dr. Kostas Alexis is a Professor at the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU), head of the Autonomous Robot Lab, and Director of the Norwegian Centre for Embodied AI. Together with his team, he conducts research on resilient robotic autonomy, exploring how autonomous systems can operate in high-risk, uncertain environments by presenting resourcefulness, robustness, and redundancy. Focusing on enhancing and safeguarding the autonomy capabilities of robotic systems, his research cuts across model-based optimization for control, sensor fusion, path planning, and learning algorithms for navigation. Prof. Alexis has served as Principal Investigator in major international grants both in Europe and the US, and was the PI and team lead of Team CERBERUS, winners of the DARPA Subterranean Challenge.
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