Tsen-Chang Lin
Papers
2
Total Citations
19
H-Index
2
About
Tsen-Chang Lin is a robotics researcher whose work bridges bio-inspired locomotion and intelligent multi-agent systems. His primary research areas include bio-inspired robotics, robot locomotion, and wireless sensor and robot networks. Lin’s most notable contribution is the model-based design and evaluation of a brachiating monkey robot equipped with an active waist, enabling continuous brachiation on swingable rods—a critical step toward mastering locomotion on soft ropes and fixed horizontal ropes. This work, cited 10 times, distinguishes itself from prior efforts by addressing dynamic stability and active body coordination. In parallel, Lin has advanced coverage control in wireless sensor and robot networks, proposing a direct learning controller that leverages the expectation maximization algorithm. This approach, cited 9 times, integrates high-level and low-level sensors on mobile robots with stationary low-level sensors to efficiently cover unknown environments. Together, these contributions showcase Lin’s ability to combine mechanical design, control theory, and probabilistic learning, making his work relevant for researchers in field robotics, environmental monitoring, and biologically inspired systems.
Research Focus
Key Achievements
Top Papers
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