Zhubang Luo
Papers
2
Total Citations
20
H-Index
2
About
Zhubang Luo is a rising researcher in the field of intelligent construction robotics, with a focus on task allocation and path planning for collaborative human-robot environments. Their work addresses critical challenges in deploying multiple construction robots on dynamic job sites, where safety and efficiency are paramount. Luo’s most-cited paper, "Two-stage task allocation for multiple construction robots using an improved genetic algorithm" (2024, 18 citations), introduces a novel optimization framework that significantly enhances coordination among robot teams, reducing idle time and improving task completion rates. In a complementary study presented at the 41st ISARC (2024), Luo and co-authors developed a path planning method that integrates safe space constraints and worker trajectory prediction, enabling robots to navigate around human workers without compromising productivity. This work has been recognized for its practical relevance to real-world construction sites, where safety is a top priority. With a growing citation impact and contributions to both algorithmic innovation and applied robotics, Zhubang Luo is establishing a strong foundation for future advancements in autonomous construction systems.
Research Focus
Key Achievements
Top Papers
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- 2