Kangchen Lv
Papers
4
Total Citations
149
H-Index
4
About
Kangchen Lv is an emerging robotics researcher whose work centers on the perception, modeling, and control of deformable linear objects (DLOs) — a challenging frontier in robotic manipulation that encompasses flexible materials such as ropes, wires, and cables. His most significant contribution lies in developing adaptive, data-driven frameworks for learning deformation models of DLOs without requiring precise theoretical calculations, enabling robots to handle objects whose physical properties vary widely across real-world settings. His 2022 paper on global model learning for large deformation control has garnered 82 citations, establishing him as a notable voice in this specialized domain. Lv has further advanced the field by tackling manipulation in constrained, obstacle-rich environments through dual-arm robotic systems capable of whole-body collision avoidance, as well as by addressing the difficult problem of 3D state estimation from occluded point cloud data using learning-based approaches. Collectively accumulating nearly 150 citations across just a few years of publication, his research bridges perception, planning, and control to bring robust DLO manipulation meaningfully closer to practical industrial and everyday applications.
Research Focus
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Top Papers
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