Lingxuan (Leo) Kong is a PhD student supervised by Dr. Alexandra Brintrup in the Manufacturing Analytics Group in Institute of Manufacturing. His current research area is on distributed learning-based control methods for supply chain and multi-agent system.

Lingxuan received his Bachelor of Engineering (Honours) degree from Australian National University. He majored in mechatronics system. His previous research projects during bachelor study mainly focus on the distributed clustering algorithm and graph partitioning techniques. These algorithms can be applied to multi-robot system and data processing problems. He also took an internship at Bernecker & Rainer Industrial. Automation. He designed a learning-based controller which combines the BP neural network learning and pole-placement control methods for the inverted pendulum.

Publications:

L. Kong, Q. Liu and C. Yu, "Range-limited distributed algorithms on higher-order Voronoi partitions in multi-robot systems", in 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, 2019

Yuni Zhou, Lingxuan Kong, Stefan Sosnowski, Qingchen Liu, Sandra Hirche" Distributed Event/Self-Triggered Coverage Control with Speed Constrained Unicycle Robots", in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, 2021