Built a GAN model based on Pix2Pix to transform point cloud projection images into camera depth images. Enables transformation between point cloud and image coordinates.
Team NCTU (7th Place). Developed autonomous mapping and navigation for underground environments using multi-agent systems.
Tracking and following marine robots using SSD (Single Shot MultiBox Detector), Kalman Filter, and PID control with visual and point-cloud data.
Deep learning classification of 3D point clouds using 2D projection images. Deployed in RobotX 2018 competition.
3D Perception Leader (5th Place). In charge of 3D LiDAR and depth camera perception, including detection and classification.
Built a self-navigating robot for campus environments using 16-bin LiDAR, IMU, GPS, and wheel odometry.
Built a 3D point cloud modeling system using PCL, ICP, iSAM, and apriltags with a single depth RGB camera.
ROS-based multi-robot patrolling system for surveillance and logistics applications.