Mengyu Ji

University of Chinese Academy of Sciences, Zhejiang University

Papers

Total Citations

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About

Mengyu Ji is a robotics researcher whose work focuses on intelligent motion planning and control for robotic systems, with particular emphasis on reinforcement learning and bio-inspired design. Her most cited paper, "A Path Planning Approach Based on Q-learning for Robot Arm" (2019, 18 citations), addresses a critical gap in applying Q-learning—a reinforcement learning method typically reserved for mobile robot navigation—to the complex, high-dimensional path planning challenges of robotic arms. This contribution has been recognized as a foundational step in expanding reinforcement learning's applicability to manipulation tasks. More recently, Ji has advanced the field with "Avian-inspired high-precision tracking control for aerial manipulators" (2024, 4 citations), where she draws inspiration from bird flight dynamics to achieve precise control in aerial robots equipped with manipulators. This work bridges the gap between biological principles and robotic precision, opening new possibilities for drones that can interact with their environment. Ji’s research is notable for its interdisciplinary approach, combining machine learning, control theory, and biomimicry to solve practical robotics challenges, making her a rising voice in the development of more capable and adaptive robotic systems.