Networked Optimization, Diagnosis and Estimation LAB

Recent publications

Learning-aided state estimation for robotic rollators with experimental validation
Robotics and Autonomous Systems, 2025. [doi]
Interaction-aware motion planning and control based on game theory with human-in-the-loop validation
Robotics and Autonomous Systems, 2025. [doi]
Adaptive and soft constrained vision-map vehicle localization using Gaussian processes and instance segmentation
Expert Systems with Applications, 264, 2025. [doi]
Visual-Inertial-Wheel Odometry with Slip Compensation and Dynamic Feature Elimination
Sensors, 25, 2025. [doi]

About us

The Networked Optimization, Diagnosis, and Estimation (NODE) Lab’s research programs aim to advance safe decision-making and motion planning for cyber-physical systems and shared human-autonomy controls, with a focus on intelligent and cooperative systems in unstructured and dynamic environments. This is achieved through fundamental research in augmented perception, networked control systems, safe reinforcement learning, and physics-informed machine learning. Within its translational and interdisciplinary research programs, the NODE lab has had knowledge development and technology transfer to various industries, including robotics, assistive technologies, intelligent transportation, and autonomous systems.