About

Rong Xiong is a prominent robotics researcher whose work spans autonomous navigation, robotic manipulation, and intelligent sensing systems. His contributions have profoundly advanced the fields of LiDAR-based localization, robot force estimation, and vision-language-action integration for robotic grasping. Xiong's foundational work on contact force estimation for robot manipulators — combining semiparametric models with disturbance Kalman filtering (147 citations) — enabled safer, more compliant human-robot interaction without requiring dedicated force sensors. In autonomous navigation, he has made landmark contributions through 3D LiDAR-based global localization using Siamese neural networks (105 citations), the differentiable scan context method DiSCO (103 citations), and the roto-translation invariant RING++ framework (72 citations), collectively pushing the boundaries of robust place recognition. His 2024 survey on global LiDAR localization (108 citations) has quickly become an essential reference for the community. Beyond navigation, Xiong has advanced robotic manipulation through reinforcement learning-based push-grasping synergy (84 citations) and joint vision-language-action modeling for language-conditioned grasping (50 citations). His survey on continuum robot design and control (94 citations) further demonstrates his breadth across robotics subfields. With over 870 cumulative citations across these ten works alone, Xiong represents a uniquely versatile and impactful voice in modern robotics research.

Research Focus

Key Achievements

24
H-Index
177
Papers
2,494
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Contact Force Estimation for Robot Manipulator Using Semiparametric Model and Disturbance Kalman Filter
147 citations · 2017
📈 Most Prolific Year: 2024 (27 Papers)
🤝 Key Collaborators: 300
🏛 Institutions: State Key Laboratory of Industrial Control Technology, Zhejiang University, University of Technology Sydney, Zhejiang University of Technology, Shenzhen Institutes of Advanced Technology, Universiti Malaysia Sarawak

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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