Yanzi Kong

Shenyang Institute of Automation

Papers

2

Total Citations

6

H-Index

2

About

Yanzi Kong is a researcher advancing the field of active perception and view planning in robotics. Her work focuses on developing intelligent systems that enable robots to autonomously adjust sensor postures for multi-view perception tasks, transforming passive observation into active, resource-efficient perception. Her key contributions include a unified optimization framework for multiple active object recognition tasks, leveraging a Feature Decision Tree to streamline decision-making processes. She also introduced a generic view planning system based on formal expression of perception tasks, which enhances robot intelligence by reducing computational and energy consumption. Though early in her career, her papers have garnered citations from peers working in robotics and computer vision, signaling growing impact. Her research lays critical groundwork for more adaptive and autonomous robotic systems, particularly in environments requiring efficient, multi-perspective sensing. Kong’s work is notable for its systematic approach to formalizing perception tasks, offering a scalable solution that bridges theoretical planning and practical robotic applications.

Research Focus

Key Achievements

2
H-Index
2
Papers
6
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Unified Optimization for Multiple Active Object Recognition Tasks with Feature Decision Tree
4 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Shenyang Institute of Automation

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago