Wenkai Sun

About

Wenkai Sun is a robotics researcher whose work centers on advancing robot perception, autonomy, and control through innovative SLAM (Simultaneous Localization and Mapping) and locomotion techniques. His most significant contribution is an Object SLAM framework that tackles the critical challenges of data association, object representation, and semantic mapping for high-level robot tasks—a paper that has garnered 47 citations since 2023. This work moves beyond traditional geometric SLAM to enable robots to understand and interact with their environment at the object level, a key step toward truly intelligent autonomous systems. Sun has also made notable strides in quadruped robot stability, developing a dynamic balance control method that adjusts foot placement during diagonal gait to improve locomotion robustness. Additionally, his research on relocalization introduces an object-plane co-represented, graph propagation-based semantic descriptor, addressing the persistent problem of appearance-based failures under changing conditions. Together, these contributions demonstrate a deep commitment to building robots that can perceive, map, and move through complex, unstructured environments with greater reliability and semantic understanding.

Research Focus

Key Achievements

Top Papers

1. 1
   An Object SLAM Framework for Association, Mapping, and High-Level Tasks

   47 citations · 2023
2. 2
   Balance Control of a Quadruped Robot Based on Foot Fall Adjustment

   14 citations · 2022
3. 3
   Object-Plane Co-Represented and Graph Propagation-Based Semantic Descriptor for Relocalization

   8 citations · 2022
4. 4
   An Object SLAM Framework for Association, Mapping, and High-Level Tasks

   2 citations · 2023

Key Collaborators

Contact & Links