Na Geng

Jiangsu Normal University, China University of Mining and Technology

Papers

Total Citations

113

H-Index

About

Dr. Na Geng is a leading researcher in the field of multi-robot systems and swarm intelligence, with a primary focus on optimizing rescue operations in disaster environments. Her work centers on developing advanced particle swarm optimization (PSO) algorithms to solve critical challenges in robot path planning and task allocation under severe time constraints. Dr. Geng’s most influential contribution is the introduction of the task allocation PSO (TAPSO) algorithm, detailed in her highly cited 2021 paper (80 citations), which provides a global optimization framework for coordinating multiple robots in rescue scenarios with uncertain time windows. She further advanced the field with her 2014 study on PSO-based robot path planning for multisurvivor rescue in limited survival time (29 citations), demonstrating how to maximize the number of survivors rescued within strict temporal limits. Her 2019 work on an improved PSO grouping method for task allocation (4 citations) continues to refine multi-robot coordination in complex post-disaster settings. With a cumulative impact of over 110 citations, Dr. Geng’s research provides practical, algorithm-driven solutions that enhance the efficiency and effectiveness of robotic rescue teams, making her a notable contributor to the intersection of computational intelligence and humanitarian robotics.