Yian Deng
Papers
7
Total Citations
41
H-Index
4
About
Yian Deng’s research lies at the intersection of developmental robotics, humanoid locomotion, and sensorimotor skill acquisition. His most influential work draws inspiration from human infant development to enable robots to autonomously acquire reaching abilities—a foundational skill for grasping and manipulation. In his highly cited 2016 and 2018 papers (11 and 10 citations, respectively), Deng proposed a novel framework grounded in embodied cognition, showing how a robot can develop reaching through a deeply embodied process rather than pre-programmed trajectories. This infant-inspired approach has been recognized as a promising paradigm for efficient, adaptive robot learning. Beyond reaching, Deng has contributed to biped robot safety with human-inspired active compliance for falling motion control (9 citations), and explored robot drumming through a listening-playing loop, real-time workpiece recognition via corner detection, and smooth target chasing for wheeled robots. His work also extends to environmental perception using Gaussian process regression. With a consistent focus on biologically inspired and compliance-based control, Deng’s research offers practical pathways for robots to interact safely and intelligently in complex, real-world environments—making his contributions valuable for both developmental robotics and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1An infant-inspired model for robot developing its reaching ability11 citations · 2016
- 2How Does a Robot Develop Its Reaching Ability Like Human Infants Do?10 citations · 2018
- 3Biped robot falling motion control with human-inspired active compliance9 citations · 2016
- 4Developing Robot Drumming Skill with Listening-Playing Loop4 citations · 2017
- 5
- 6Learning to chase a ball efficiently and smoothly for a wheeled robot2 citations · 2017
- 7Humanoid environmental perception with Gaussian process regression2 citations · 2016