Working on predictive world model based on xmotors’ VLA2.0. Worked on static perception of autonomous driving system.

Worked on semantic occupancy grid

3D perception, planning

Realizing “Driver Monitoring System” with facial recognition utilizing machine learning.

Establishing facial expression classifiers by training convolution neural network with Python and realizing facial expression recognition algorithm in C/C++.

Implementing “Driver Monitoring System” with NXP S32 and Nvidia Jetson TX2 Micro Processor.

• Realized sensor data collection system collecting multiple sensors’ data from serial ports and CAN bus before transferring data to the back-end with Realtime Control System (RCS) based on Neural Message Language (NML).

• Designed and realized an error detecting and alerting system to guarantee the correctness of data collected by the Simultaneous Localization and Mapping (SLAM) vehicle supporting both online and offline modes.

• Tested and evaluated multiple sensors including cameras, IMU, GPS and NTP servers.

• Accomplished integration of visual perception toolkit and NML with C++ on Nvidia PX2.