Xiangting Cai

National University of Defense Technology

Papers

1

Total Citations

16

H-Index

1

About

Xiangting Cai is a leading researcher in robotic manipulation and computer vision, with a primary focus on grasp detection and perception for autonomous systems. Their most notable contribution is the development of SymmetryGrasp, a pioneering learning-based method that leverages object symmetry to improve antipodal grasp detection from single-view RGB-D images. By recognizing that humans naturally grasp objects through symmetric regions, Cai’s work introduces a novel approach that significantly enhances robotic grasping accuracy and robustness. This research, published in 2022, has already garnered 16 citations, demonstrating its growing influence in the field. Cai’s work bridges the gap between human intuition and machine perception, offering practical solutions for real-world robotic applications. Their contributions are particularly impactful for industries requiring precise object handling, such as manufacturing and logistics. With a strong foundation in deep learning and 3D vision, Xiangting Cai continues to advance the state of the art in robotic manipulation, making their research essential reading for students and engineers interested in intelligent grasping systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
16
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
SymmetryGrasp: Symmetry-Aware Antipodal Grasp Detection From Single-View RGB-D Images
16 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: National University of Defense Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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