Ziwu Ren
Papers
6
Total Citations
52
H-Index
4
About
Ziwu Ren is a leading researcher in intelligent robotics, specializing in multirobot coordination, manipulator trajectory planning, and reinforcement learning-based control. Ren's most impactful work, "Distributed Multirobot Path Planning Based on MRDWA-MADDPG" (21 citations), introduces a novel distributed multiagent deep reinforcement learning framework that integrates a multirobot dynamic window approach with MADDPG, enabling robust path planning in complex, dynamic environments. This contribution addresses a critical challenge in multirobot systems by facilitating decentralized, collision-free navigation. Ren has also made significant advances in manipulator control, including a knowledge database-based multiobjective trajectory planning method for 7-DOF manipulators (14 citations) that achieves rapid, continuous response to uncertain fast-flying objects, and a parameterization-based approach for 8-DOF manipulators with multiple constraints (6 citations). Further work on hybrid electromagnetism-like mechanism algorithms for inverse kinematics and adaptive sliding mode control based on reinforcement learning demonstrates Ren's breadth in combining optimization, control theory, and machine learning. With over 50 total citations, Ren's research is shaping the future of autonomous robotic systems, offering practical solutions for high-DOF manipulators and multirobot coordination in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1Distributed Multirobot Path Planning Based on MRDWA-MADDPG21 citations · 2023
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