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KAIST Cho Chun Shik Graduate School of Mobility
Welcome
Welcome
Complexity and inter-connectivity are the main characteristics of the critical societal challenges including future mobility. Improvement of autonomy will be crucial to properly overcome these challenges. Especially, networked autonomy will be the key for the future mobility.
Autonomous and Intelligent Systems Laboratory (AIS Lab) intends to resolve these challenges by making continuous contributions on the following research areas:
Operations of unmanned/autonomous systems in complex environments, e.g., urban areas
Cooperation of multiple/networked unmanned systems
Development of Information-driven approaches
Publication
Publication
Journal Articles
Review of data-driven computational guidance for unmanned aerospace vehicles (Progress in Aerospace Sciences, 2025)
Field-of-View Reduced Impact Angle Guidance Law via Range Shaping Approach (IEEE Trans. Aerospace and Electronic Systems, 2025)
Adaptive dual-loop disturbance observer-based robust model predictive tracking control for autonomous hypersonic vehicles
(IEEE/CAA J. Automatica Sinica, 2025)Complementary Filter-Based Incremental Nonlinear Model Following Control Design for a Tilt-Wing UAV (Int. J. Robust Nonlinear Control, 2025)
A review of Bayes filters with machine learning techniques and their applications (Information Fusion, 2025)
Conference Papers
Towards Autonomous Landing on Dynamic Naval Surfaces Under Harsh Sea State Motion (AIAA SCITECH, 2025)
A Passivity-Based Method for Accelerated Convex Optimisation (IEEE CDC, 2024)
Cross-Observability Learning for Vehicle Routing Problems (IEEE IROS, 2024)
Π-ORFit: One-Pass Learning with Bregman Projection (ACC, 2024)
Deep Reinforcement Learning-Based Neighbor Selection of a Cucker-Smale Flocking Algorithm (CoDIT, 2024)
Distributed Neighborhood Search Algorithm for Target Assignment (ECC, 2024)
Recursive Least Squares with Log-Determinant Divergence Regularisation for Online Inertia Identification (ICRA, 2024)
Gallery
Gallery
Seminar Calendar
Seminar Calendar
Prospective Students
Prospective Students
We are recruiting MSc/PhD graduate students interested in autonomy, artificial intelligence, and information-driven systems and control on future mobility.
Contact hyosangshin@kaist.ac.kr to get more information.
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