Sihang Yang

Nanjing University of Information Science and Technology

Papers

Total Citations

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About

Sihang Yang is a robotics researcher whose work focuses on advancing autonomous manipulation in cluttered, real-world environments. His key research areas include object-oriented planning, robot learning, and task-level control for domestic service robots. Yang’s most notable contribution is the **Object-Oriented Option Framework**, introduced in his 2023 paper, which provides a structured approach to decomposing complex manipulation tasks into reusable, object-centric subroutines. This framework enables robots to more efficiently plan and execute actions in cluttered spaces—a longstanding challenge in robotics due to the high-dimensional state and action spaces involved. By bridging hierarchical reinforcement learning with object-level reasoning, Yang’s work offers a scalable solution for robots to handle everyday household tasks like sorting, stacking, or retrieving items from crowded bins. His research has already garnered early citations (6 for his flagship paper), signaling growing interest from the manipulation and learning communities. Yang’s contributions are particularly timely as the demand for capable domestic robots rises, and his framework lays important groundwork for more adaptive, generalizable robotic helpers.