Guiliang Zheng

University of Washington

Papers

2

Total Citations

4

H-Index

2

About

Guiliang Zheng is an emerging researcher working at the intersection of robotics, tactile sensing, and machine learning. His work focuses on enabling robotic systems to achieve human-like dexterity in object grasping and manipulation — a fundamental challenge in modern robotics. Rather than relying on conventional vision-based approaches, Zheng's research pioneers the use of tactile feedback to detect slip during robotic gripping tasks, a capability critical for reliable object handling in unstructured environments. His most notable contribution involves developing a learning-based framework that estimates the contact force field and analyzes its entropy properties to detect slip events in real time. This innovative approach moves beyond visual sensing paradigms, pushing robotic tactile perception closer to the nuanced sensitivity of human touch. Published across 2023 and 2024, this line of work has already begun attracting attention within the robotics community, accumulating early citations that signal growing interest in tactile-driven manipulation strategies. Though still early in his research career, Zheng's focus on bridging the gap between human and robotic manipulation proficiency positions him as a promising contributor to the fields of haptic sensing, robot learning, and intelligent manipulation systems. His work offers meaningful foundations for future advances in dexterous robotic hands and autonomous manipulation.

Research Focus

Key Achievements

2
H-Index
2
Papers
4
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Learning to Detect Slip through Tactile Estimation of the Contact Force Field and its Entropy
2 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: University of Washington

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago