Xuemei He

Xi'an University of Science and Technology

Papers

Total Citations

H-Index

About

Dr. Xuemei He is a leading researcher in autonomous robotics and intelligent navigation systems, with a particular focus on deep reinforcement learning for real-world applications. Her most-cited work, "Intelligent Navigation of Indoor Robot Based on Improved DDPG Algorithm" (2023, 5 citations), addresses a critical challenge in robotics: enabling autonomous decision-making in large-scale, complex, and unknown indoor environments. By enhancing the Deep Deterministic Policy Gradient (DDPG) algorithm, Dr. He has developed a method that allows robots to navigate without relying on pre-built environment models—a significant departure from traditional path planning approaches. This contribution is pivotal for advancing service robots, warehouse automation, and assistive technologies. Her work bridges the gap between theoretical reinforcement learning and practical deployment, demonstrating how AI-driven agents can learn robust navigation policies through trial and error. Dr. He's research not only improves the efficiency and adaptability of indoor robots but also lays the groundwork for more intelligent, self-sufficient systems in dynamic settings. With a growing citation impact, her innovations are shaping the future of autonomous navigation and inspiring new directions in robotic intelligence.