Papers
2
Total Citations
50
H-Index
2
About
Kewei Li is a robotics and computer vision researcher whose work spans multi-robot coordination, underwater imaging, and intelligent marine systems. Li's foundational contribution in multi-robot systems, the Virtual Spring Method for multi-robot path planning and formation control (2019), has garnered 46 citations, establishing a practical and elegant framework for coordinating robot swarms by modeling inter-robot relationships as virtual mechanical springs — enabling smooth, collision-aware formation navigation without complex centralized computation. Building on this foundation in autonomous systems, Li has more recently turned attention to the challenging domain of underwater robotics and marine intelligence. Their 2024 work introducing a Multi-Scale Convolutional Hybrid Attention Residual Network addresses the notoriously difficult problem of underwater image degradation — particularly color distortion — applying the model to sea cucumber detection across varied underwater scenes. This research reflects a broader vision of deploying autonomous underwater vehicles to replace dangerous manual marine labor. Across their career, Li demonstrates a consistent drive to solve real-world deployment challenges for robots operating in unstructured environments, bridging classical control theory with modern deep learning to push the boundaries of autonomous systems in both terrestrial and subsea applications.
Research Focus
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Top Papers
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