Yujiao Cheng
Papers
8
Total Citations
267
H-Index
6
About
Yujiao Cheng is a leading researcher in human-robot collaboration (HRC), focusing on making industrial robots truly intelligent partners rather than mere tools. Her work centers on three interconnected challenges: plan recognition, motion prediction, and human-aware task planning. Cheng’s most impactful contribution is her 2020 paper on efficient HRC with robust plan recognition and trajectory prediction (98 citations), which addresses the manufacturing shift from mass production to mass customization. She developed novel approaches using semi-adaptable neural networks for human motion prediction (52 citations) and hierarchical task models for human-aware robot planning (55 citations), enabling robots to anticipate human actions and adapt their own plans accordingly. Her research on predicting human arm targets for robot reaching movements (26 citations) and long-term hand trajectory prediction (15 citations) has been crucial for safe, efficient collaboration in shared workspaces. Through her SERoCS framework (15 citations), Cheng has advanced the design of safe and efficient collaborative robotic systems for next-generation industrial co-robots. Her work consistently tackles the fundamental challenge of enabling robots to operate effectively in dynamic, uncertain environments alongside human collaborators, making her a key figure in the future of intelligent manufacturing.
Research Focus
Key Achievements
Top Papers
- 1
- 2Human-Aware Robot Task Planning Based on a Hierarchical Task Model55 citations · 2021
- 3Human Motion Prediction using Semi-adaptable Neural Networks52 citations · 2019
- 4Prediction of Human Arm Target for Robot Reaching Movements26 citations · 2019
- 5
- 6
- 7Human Motion Prediction using Semi-adaptable Neural Networks4 citations · 2018
- 8Human-Aware Robot Task Planning with Robot Execution Time Estimation2 citations · 2022