Lingjie Lin
Papers
3
Total Citations
11
H-Index
2
About
Lingjie Lin is a researcher at the forefront of aerospace human-robot interaction, specializing in virtual training systems for astronauts. Their work addresses critical challenges in simulating complex, multi-person cooperative tasks in space, particularly the handling of massive objects where precise coordination is essential. Lin’s major contributions include developing high-order dynamic constraints for velocity planning in astronaut virtual training robots, ensuring safe and efficient motion during simulated object transport. They have also pioneered algorithms to estimate 6-dimensional virtual human-machine interaction forces, effectively mapping keyboard and mouse inputs into realistic force feedback—a breakthrough that replaces costly physical sensors with virtual ones. This innovation, detailed in their 2023 and 2022 papers, enables more accurate and accessible ground-based training. Though their citation counts are modest (6, 3, and 2 for their top papers), Lin’s work is foundational for next-generation astronaut preparation, directly supporting China’s space station missions. Their research bridges robotics, virtual reality, and human factors, offering practical solutions for high-stakes space operations. For students and researchers in aerospace engineering or VR, Lin’s work exemplifies how algorithmic innovation can transform training paradigms for extreme environments.
Research Focus
Key Achievements
Top Papers
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- 3