Tan Xin
Papers
1
Total Citations
25
H-Index
1
About
Tan Xin is a leading researcher in multi-robot systems and legged locomotion, with a focus on enabling coordinated, autonomous patrol tasks using quadruped robots. Their major contribution lies in the development of optimization-based distributed flocking controllers and model predictive control (MPC)-based gait synchronization techniques, which allow multiple quadruped robots to move cohesively and adapt their gaits in real time—a critical capability for real-world surveillance and search-and-rescue missions. Their most-cited work, "Optimization-Based Flocking Control and MPC-Based Gait Synchronization Control for Multiple Quadruped Robots" (2024), has already garnered 25 citations, reflecting its immediate impact on the robotics community. This paper stands out for its novel integration of flocking theory with predictive control, addressing both high-level coordination and low-level locomotion stability. Tan Xin’s research bridges the gap between theoretical multi-agent control and practical robotic deployment, offering scalable solutions for dynamic environments. Their work is essential reading for students and engineers interested in swarm robotics, legged locomotion, and real-time optimization, and it positions them as an emerging authority in the field of cooperative robotic systems.
Research Focus
Key Achievements
Top Papers
- 1