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