Papers
2
Total Citations
13
H-Index
2
About
Qiuhua Li is a leading researcher in intelligent robotics and autonomous navigation, with a focus on path planning and obstacle avoidance for complex environments. Their major contributions include the development of a hybrid path planning algorithm that integrates a modified golden jackal optimization method with the dynamic window approach, significantly improving robot navigation efficiency and safety in dynamic settings. This work, published in 2025, has already garnered 9 citations, reflecting its immediate impact on the field. Li has also advanced deep-sea exploration by proposing a learning-based obstacle avoidance strategy for remotely operated vehicles (ROVs) used in mining, a paper that has earned 4 citations since its 2025 publication. These contributions demonstrate Li’s ability to bridge optimization techniques and machine learning for real-world robotic applications, from terrestrial robots to underwater vehicles. Their research is particularly notable for addressing the challenges of autonomous operation in hazardous and unstructured environments, positioning them as an emerging authority in intelligent robotics and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2