A novel approach for mapping and localization in dynamic indoor environments, enhancing SLAM performance through adaptive multimode techniques.

Z. Lin, Q. Zhang, Z. Tian, P. Yu, Z. Ye, H. Zhuang, J. Lan

Pattern Recognition, 2025

Presents an advanced Visual SLAM system optimized for safe navigation in lightweight autonomous vehicles, ensuring collision avoidance in complex environments.

Z. Lin, Z. Tian, Q. Zhang, H. Zhuang, J. Lan

Sensors, 2024

Introduces a data-driven approach to enhance adaptive cruise control in complex, nonlinear vehicle platoons for improved safety and efficiency.

J. lan

IET Intelligent Transport Systems, 2024

This paper enhances Point-Line SLAM by integrating dense semantic data for improved accuracy in dynamic environments.

Zhihao Lin, Qi Zhang, Zhen Tian, Peizhuo Yu, Jianglin Lan

IEEE Sensors Journal, 2024

Presents a comprehensive planning approach for automated driving that accounts for safe interactions with human drivers.

Harikirshnan Vijayakumar, Dezong Zhao, Jianglin Lan, Wenjing Zhao, Daxin Tian, Dachuan Li

IEEE Transactions on Intelligent Vehicles, 2023

Proposes a real-time framework for vehicle tracking using multiple cameras, improving accuracy and robustness in dynamic environments.

Hanyang Zhuang; Xingyuan Chen; Jianglin Lan; Ying Wang; Zhaoxuan Lu; Chunxiang Wang

2024 IEEE International Conference on Real-time Computing and Robotics

This paper presents a method for ensuring safe real-time control of dynamic models using neural networks with robust approximation techniques.

Hanjiang Hu, Jianglin Lan, Changliu Liu

Proceedings of Machine Learning Research vol 242:92–103

Introduces a distributed control strategy aimed at maximizing energy extraction from an array of wave energy converters.

S. Zhan, Y. Chen, J. Lan, and Y. Zhang

2024 UKACC 14th International Conference on Control

Proposes a method for generating robust and plausible counterfactual explanations for neural networks using robust optimization techniques.

J. Jiang, J. Lan, F. Leofante, A. Rago, and F. Toni

Proceedings of the 15th Asian Conference on Machine Learning, 2024

This paper presents a data-driven dual-loop control strategy for platooning, addressing the integration of human-driven and automated vehicles in the same platoon.

Jianglin Lan

IET Intelligent Transport Systems, 1–10, 2023

This paper explores the determination of optimal Linear Quadratic Regulator (LQR) weights to ensure a common solution to the associated Riccati equations.

J. Lan, D. Zhao

IEEE Transactions on Automatic Control, 68(10) 6393–6400, 2023

Presents a framework for real-time safety monitoring and alerting in control systems powered by neural networks.

Jianglin Lan

IFAC Word Congress, IFAC-PapersOnLine, 56(2), 9436-9441, 2023

This paper introduces an iterative approach using semidefinite relaxations to improve the efficiency and accuracy of neural network verification.

Jianglin Lan, Yang Zheng, Alessio Lomuscio

Proceedings of the AAAI Conference on Artificial Intelligence, 37(12), 14937-14945, 2023

Proposes a branch-and-bound method using semidefinite relaxation to achieve tighter and more reliable neural network verification.

Jiaglin Lan, Benedikt Bruckner, Alessio Lomuscio

Proceedings of the AAAI Conference on Artificial Intelligence Vol. 37 No. 12, 2023

This paper develops a cooperative control policy for mixed vehicle platoons, emphasizing safety and robustness in data-driven approaches.

Jianglin Lan, Dezong Zhao, Daxin Tian

International Journal of Robust and Nonlinear Control, 33(7), 4171–4190, 2023

Presents an iterative approach to enhance fault estimation and integrate fault-tolerant control, improving system resilience.

Jianglin Lan, Ron Patton

Automatica, Volume 145, 110556, 2022

Presents an iterative approach to enhance fault estimation and integrate fault-tolerant control, improving system resilience.

Jianglin Lan, Yang Zheng, Alessio Lomuscio

Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 36 No. 7, 2022

This paper develops a robust predictive control strategy for mixed vehicle platoons, focusing on handling noisy measurements for improved performance.

Jianglin Lan, Dezong Zhao, Daxin Tian

IEEE Transactions on Intelligent Transportation Systems, 24(6) 6586 – 6596, 2021