Autonomous and Intelligent Systems Laboratory
KAIST Cho Chun Shik Graduate School of Mobility
Information-Driven Approaches
It is widely accepted that autonomous systems inherently and irreducibly artificially intelligent systems and they have to handle ever increasing data, i.e. Big Data. Therefore, AIS Lab has focused on leveraging state-of-the-arts in artificial intelligence and Big Data into the research fields he has initiated.
Future mobility is expected to be more efficient and safe. High availability systems must tolerate both expected and unexpected faults. Their design is based on redundant hardware and software combined in ways that will achieve greater availability. AIS Lab has initiated the investigation of computationally efficient and fully analytical methods, leading both the theoretical and experimental aspects of the work.
Research Projects
LANDOne - Towards Artificial Intelligence Enabled Landing Gear with Trustworthy Autonomy, funded by ATI, 2023-2026
Adaptive flight control to enhance survivability & availability, funded by BAE Systems, 2019-2022
Real-time Decision Making for Autonomous Systems, funded by US Air Force, 2019-2022
Trajectory Optimisation using Reinforcement Learning, funded by Inha University, 2019-2020
AIRMES - Airline Maintenance Operations implementation of an E2E Maintenance Service Architecture and its enablers, funded by Horizon 2020, 2016-2019
Decentralised Decision Making and Distributed Path Planning: Bio-Inspired Approach, funded by CNU, 2015-2017
Data to Information: Information Fusion for Contextual Awareness Enhancement, funded by Selex ES, 2013-2013