Mingwei Sheng

Harbin Engineering University

Mingwei Sheng's research contributes significantly to the fields of autonomous underwater vehicles (AUVs), deep learning, and control systems. Studies on tracking control for AUVs in hydrothermal fields and underwater visual tracking leverage modeling trajectory techniques and convolutional neural networks to improve navigation and object detection capabilities. The development of a joint framework for stitching underwater sequence images, adaptive terminal sliding-mode control, and clustering cloud-like model-based targets aim to enhance AUV performance and robustness. Additionally, innovative solutions for real-time body tracking, wall-following control, and piezoelectric actuated lubrication generators are presented, showcasing the researcher's expertise in advancing AUV technology and mechanisms for space applications.