Zhu Duan
Papers
2
Total Citations
12
H-Index
2
About
Zhu Duan is a researcher at the forefront of intelligent robotics and IoT systems, specializing in trajectory prediction and navigation for mobile robots in smart environments. His work addresses critical challenges in building digital twin systems and ensuring high-performance, safe robot navigation. Duan’s major contributions include the development of novel hybrid computing frameworks that integrate advanced signal processing, feature selection, and multi-objective optimization with machine learning models. His most cited paper, “Multi-Objective Multi-Learner Robot Trajectory Prediction Method for IoT Mobile Robot Systems” (2022, 10 citations), introduces a pioneering two-stage multi-learner model that significantly enhances prediction accuracy for IoT mobile robots. In earlier work, “Hybrid Position Forecasting Method for Mobile Robot Transportation in Smart Indoor Environment” (2019, 2 citations), he proposed the EWT-MOFEPSO-MRMRMI-ORELM framework, a sophisticated hybrid model for indoor position forecasting. Duan’s research is pivotal for advancing autonomous navigation, improving both the robustness and efficiency of mobile robot systems in complex indoor environments, and his innovative methodologies continue to influence the field of intelligent robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2