Zhaowei Ma

National University of Defense Technology

Papers

Total Citations

H-Index

About

Zhaowei Ma’s research bridges the frontiers of bio-inspired robotics and autonomous aerial systems, with a focus on biomimetic propulsion, visual odometry, and reinforcement learning for unmanned vehicles. His early work on robotic fish introduced an experimental-numerical approach to evaluate fin-ray trajectory tracking in bio-inspired undulating fins—a key contribution to understanding wave-like propulsion inspired by ribbon-finned fish, which has informed aquatic robotic design. Transitioning to aerial robotics, Ma pioneered the use of off-the-shelf smartphones as lightweight, low-cost sensor platforms for micro-UAV localization, demonstrating 2D monocular visual odometry that leverages built-in cameras and motion sensors. His most cited work (8 citations) on biomimetic fins remains a foundational reference in the field. Further advancing autonomous navigation, Ma developed a vision-based reactive avoidance system for UAVs using reinforcement learning, proposing an actor-critic algorithm that maps visual input directly to control actions—a novel integration of learning-based behavior with classical reactive control. With over 17 cumulative citations across these three core studies, Ma’s interdisciplinary contributions have advanced both underwater propulsion and aerial autonomy, offering practical, sensor-efficient solutions for next-generation robotic systems.