Papers
3
Total Citations
67
H-Index
2
About
Zhenyu Tang is a robotics researcher whose work bridges the gap between generalizable robotic manipulation and precision agricultural automation. His most impactful contribution is the RH20T dataset (2024, 55 citations), a comprehensive robotic dataset that enables one-shot imitation learning and the development of robotic foundation models. By providing diverse, real-world demonstrations, RH20T allows robots to acquire and transfer manipulation skills to novel tasks without extensive retraining—a critical step toward open-domain robotic autonomy. Tang also advances field robotics with a vision-based trajectory generation and tracking algorithm for paddy field robots (2024, 10 citations), enabling precise maneuvering in unstructured agricultural environments. His PRSGNet framework (2025, 2 citations) further demonstrates his commitment to robust perception, offering a crop row detection system that performs reliably under complex field conditions. Through these contributions, Tang is shaping the future of robotics—from generalist manipulation systems that learn from few examples to specialized agricultural robots that operate autonomously in challenging real-world settings.
Research Focus
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Top Papers
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