Papers
1
Total Citations
5
H-Index
1
About
Shan Ren is a researcher in multi-robot systems, with a focus on bearing-based localization and formation control. Their work addresses fundamental challenges in cooperative robotics, particularly how teams of robots can maintain formation using only directional measurements rather than full position data. In their highly cited 2017 paper, Ren studied the observability of leader-follower robot systems, demonstrating that a leader robot can achieve complete system observability by observing just two distinct landmarks. This contribution provides a theoretical foundation for more efficient and robust formation control in GPS-denied environments. While their citation count is still growing, Ren's work represents an important step toward practical deployment of autonomous robot teams in real-world scenarios such as search-and-rescue, environmental monitoring, and industrial automation. Their research bridges control theory and robotics, offering elegant solutions to the challenges of decentralized coordination with limited sensing capabilities.
Research Focus
Key Achievements
Top Papers
- 1Bearing-based localization for leader-follower formation control5 citations · 2017