Jinglan Piao

Papers

Total Citations

H-Index

About

Jinglan Piao is a robotics researcher whose work focuses on enabling robots to perform everyday manipulation tasks in unstructured environments. Her key research areas include robotic perception, pose estimation, and autonomous object manipulation, particularly for domestic service applications. Piao’s most notable contribution is her pioneering work on robotic tidy-up tasks using point cloud-based pose estimation, where she developed algorithms that allow robot arms to estimate the poses of common household objects without requiring pre-existing CAD models—a critical limitation in real-world settings. This innovation, detailed in her 2020 paper, has garnered 2 citations and lays essential groundwork for practical home robotics. By addressing the challenge of unknown object handling, Piao’s research bridges the gap between industrial automation and everyday assistive robotics, offering scalable solutions for clutter-clearing and organization tasks. Her work is particularly impactful for researchers in service robotics and human-robot interaction, as it provides a foundation for more adaptable and autonomous domestic robots. Piao’s contributions highlight the importance of perception-driven manipulation in making robots truly useful in daily life.