Yuanhai Zhou

Papers

Total Citations

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About

Yuanhai Zhou is a robotics researcher whose work centers on human-robot interaction and autonomous task planning, with a particular focus on integrating computer vision and knowledge-based reasoning. His most cited paper, "Depth-aware gaze-following via auxiliary networks for robotics" (2022, 32 citations), addresses a critical challenge in social robotics: predicting where a person is looking. Zhou’s key contribution is a method that leverages depth and orientation cues without requiring additional training datasets, streamlining the inference process for more practical robotic applications. This work has been cited by researchers in human-robot collaboration and assistive robotics. In his second notable paper, "Robot Planning based on Behavior Tree and Knowledge Graph" (2022, 5 citations), Zhou proposes a novel framework that combines behavior trees with knowledge graphs to enable robots to automatically generate and refine task plans. This approach moves beyond traditional planning methods by allowing robots to reason about their environment and adapt strategies dynamically. Zhou’s research is characterized by its focus on making robots more perceptive and autonomous, bridging the gap between low-level perception and high-level decision-making. His work holds promise for applications in service robotics, manufacturing, and collaborative environments.