Yen‐Cheng Liu

Papers

Total Citations

187

H-Index

About

Yen-Cheng Liu is a leading researcher in collaborative perception for multi-robot systems, with a focus on enabling agents to intelligently share and fuse sensory data. His seminal work, "Who2com: Collaborative Perception via Learnable Handshake Communication" (2020, 164 citations), introduces a novel framework where robots learn to selectively communicate—deciding which neighbors to exchange observations with—dramatically improving perception accuracy in cluttered or occluded environments. This foundational contribution redefines how autonomous systems can cooperate under real-world constraints. Building on this, Liu’s "Overcoming Obstructions via Bandwidth-Limited Multi-Agent Spatial Handshaking" (2021, 21 citations) tackles the critical challenge of collaborative semantic segmentation when communication bandwidth is severely limited and visual obstructions are present. By developing efficient handshake protocols for unregistered swarm imagery, his work directly addresses practical deployment hurdles in search-and-rescue, autonomous driving, and environmental monitoring. Liu’s research not only advances the theoretical underpinnings of multi-agent perception but also provides scalable, bandwidth-aware solutions that push the boundaries of what distributed robotic teams can achieve. His contributions are essential reading for anyone working at the intersection of robotics, computer vision, and multi-agent systems.