Papers
1
Total Citations
6
H-Index
1
About
Sicong Pu is a researcher whose work lies at the intersection of robotics, haptics, and sensorimotor control, with a particular focus on advancing robotic in-hand manipulation for real-world applications like service and domestic tasks. Their most cited work, "Haptic and visual perception in in-hand manipulation system" (2015, 6 citations), tackles a fundamental challenge in robotics: the uncertainty of interaction states during dexterous object handling. By integrating haptic and visual feedback, Pu’s research addresses critical gaps in how robots perceive and adapt to dynamic contact conditions, moving beyond idealized simulations toward more robust, practical systems. This contribution is especially relevant for enabling robots to perform everyday household skills—such as grasping, rotating, or reorienting objects—where precision and adaptability are paramount. While the citation count reflects an emerging impact, the work’s focus on multimodal perception and state estimation positions it as a foundational step toward more autonomous and reliable manipulation. Pu’s research underscores a commitment to bridging the gap between theoretical frameworks and real-world robotic dexterity, offering valuable insights for engineers and scientists working on service robotics, human-robot interaction, and sensor fusion.
Research Focus
Key Achievements
Top Papers
- 1Haptic and visual perception in in-hand manipulation system6 citations · 2015