Jianhao Lv
Papers
7
Total Citations
143
H-Index
5
About
Jianhao Lv is a leading researcher in human–robot collaboration (HRC), focusing on integrating artificial intelligence, digital twins, and augmented reality to create adaptive, intelligent manufacturing systems. His major contributions lie in developing graph-based and hierarchical reinforcement learning frameworks that enable robots to dynamically adjust assembly and disassembly operations in real time, moving beyond pre-programmed tasks. Lv’s work on digital twin-driven flexible scheduling and multimodality scene graph generation has significantly enhanced robots’ ability to perceive and reason about complex collaborative environments, addressing critical gaps in interactive relationship representation. With over 140 citations across his most-cited papers, including a 2022 study on graph-based reinforcement learning (56 citations) and a 2023 work on digital twin scheduling (32 citations), his research has had substantial impact. Notably, his 2025 paper on using large language models and knowledge graphs for rescheduling under dynamic disassembly scenarios represents a cutting-edge advance. Lv’s achievements include pioneering cognition-driven decision-making methods and MR-assisted scene perception systems for power battery disassembly, positioning him as a key innovator in making HRC safer, more efficient, and truly adaptive for modern manufacturing.
Research Focus
Key Achievements
Top Papers
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