Papers
1
Total Citations
34
H-Index
1
About
Yida Niu is a rising roboticist whose work sits at the intersection of manipulation planning, 3D scene understanding, and task-level reasoning. In their most cited work, “Sequential Manipulation Planning on Scene Graph” (2022, 34 citations), Niu introduced a novel 3D scene graph representation called contact graph⁺ (cg⁺) that encodes both geometric and topological relationships between objects. This representation enables robots to efficiently reason about long-horizon, multi-step manipulation tasks—such as rearranging cluttered environments—by decomposing complex problems into manageable subproblems. The cg⁺ framework directly addresses the scalability challenge in sequential manipulation, allowing planners to handle scenes with dozens of objects without exponential blowup. Niu’s contributions are particularly impactful for real-world applications like warehouse automation and assistive robotics, where robots must physically interact with their surroundings over extended sequences. By bridging high-level symbolic planning with low-level geometric constraints, Niu has opened new pathways for more intelligent and adaptable robotic systems. Their work continues to influence researchers in task and motion planning, and the cg⁺ representation has been adopted in subsequent studies on interactive perception and rearrangement planning.
Research Focus
Key Achievements
Top Papers
- 1Sequential Manipulation Planning on Scene Graph34 citations · 2022