Selected Research Project

  • Cooperative localization for vehicles in GNSS denied environment (PI) 2022.01-2024.12
    • Localization enhancement for INS
    • Multi sensor fusion for robot localization in challenging outdoor environments.
    • Multi-vehicle cooperative for the remove of accelerative error.
  • Cooperative localization for air-ground amphibious vehicles (Co-PI) 2020.11-2024.12
    • Key Project supported by the Ministry of Science and Technology, China.
    • Multi-sensor fusion for the localization of air-ground amphibious vehicles.
    • Cooperative localization and mapping in GNSS denied environment.
    • Cooperative trajectory planning for multi-air-ground amphibious vehicles.
  • Information fusion and environmental cognition for intelligent vehicle (Co-PI) 2021.01-2024.12
    • Key Project supported by NSFC, China
    • Multi-sensor fusion for localization of autonomous vehicles
    • Information fusion for environmental cognition
  • Cooperative multi-vehicle localization (PI) 2021.01-2023.12
    • Supported by NSFC, China
    • Fusion of GPS and IMU signals for single vehicle localization.
    • Radar for relative localization and UWB for V2V communication.
    • Information fusion for better global cooperative localization.
  • Control for wheel independent motor-drive electric vehicle (PI) 2018.11-2021.12
    • Supported by National Key Laboratory
    • Research on the performance limit and the envelope control of WIMD vehicles.
    • Fault-tolerant control for WIMD vehicles.
  • Sensor networks for energy efficient air-conditioning system (Collaborator) 2017.01-2018.10
    • Sensor networks provide the real-time environmental parameters.
    • Thermal camera and wearable sensors provide users’ parameters.
    • The optimal set-point can be found based on the sensor observations and thermal comfort model.
  • Occupancy estimation and human activity recognition (Collaborator) 2015.01 -2018.10
    • Historical occupancy data are used to build an occupancy model.
    • Non-intrusive environmental sensors are used to estimate occupancy level.
    • Smart phone is used for human activity recognition.
  • Visualization of smart building based on sparse senor observations 2013.01-2017.09
    • Subspace projection optimization for optimal sensing locations design.
    • Sparse indoor sensors are used to estimate indoor thermal map and airflow patterns.
    • Indoor thermal map and airflow patterns are used to assess the building energy efficiency.
  • Visualization of smart building based on sparse senor observations 2009.09-2011.06
    • State constraints can be used to improve the state estimates
    • Linear equality state constraints correspond to a determined subspace of the system state space
    • Most of the current approaches are summed up into a unified framework