Yingnan Gao

Wuhan University of Science and Technology

Papers

Total Citations

H-Index

About

Yingnan Gao is a researcher specializing in robotics, computer vision, and autonomous systems, with a particular focus on mobile robot control and target acquisition in dynamic environments. Their most notable contribution is the development of a mobile robot automatic aiming method based on binocular vision, which enables robots to autonomously identify, track, and accurately shoot projectiles at moving targets in complex, adversarial settings. This work, published in 2021, introduces an improved object detection algorithm that extracts two-dimensional position coordinates and integrates them with real-time control systems, addressing critical challenges in robotic precision and responsiveness during confrontation scenarios. While the paper has garnered 4 citations to date, its significance lies in advancing the intersection of visual perception and autonomous decision-making for defense and competitive robotics applications. Gao’s research pushes the boundaries of how robots interact with unpredictable environments, offering foundational insights for future developments in automated targeting, human-robot collaboration, and intelligent mobility. Their work is particularly relevant for students and engineers exploring real-time vision-based control in high-stakes, dynamic settings.