Qi Lv

Chongqing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Qi Lv is a researcher whose work bridges robotics, optimization, and surgical automation. Their key research areas include path planning for mobile robots, swarm intelligence algorithms, and skill learning for robotic-assisted surgery. Lv’s major contributions include developing an improved particle swarm optimization (PSO) algorithm for multi-target path planning, which enhances robot navigation efficiency through inverse learning initialization and dynamic parameter adjustment. This work has garnered 14 citations, reflecting its relevance in autonomous robotics. In surgical robotics, Lv pioneered a reusable suturing skill model using dynamical movement primitives and learning from demonstration, enabling automatic skill evaluation and transfer in robotic-assisted surgery. This study, with 9 citations, advances the modeling of complex surgical tasks, offering significant potential for training and automation. Lv’s work is notable for integrating optimization techniques with practical robotic applications, from mobile robot navigation to delicate surgical procedures. Their research not only improves algorithmic performance but also contributes to the growing field of intelligent robotic systems, making their profile valuable for students and researchers interested in robotics, optimization, and medical technology.