Kaiqi Zhang
Papers
1
Total Citations
6
H-Index
1
About
Kaiqi Zhang is a researcher focused on advancing agricultural robotics and human-robot collaboration, with a particular emphasis on mechanized operations in forestry and plantation environments. His work centers on developing intelligent path planning methods for specialized tasks, such as trenching in Camellia oleifera forests—a key crop for edible oil production. In his most-cited paper, "Path planning method for Camellia oleifera forest trenching operation based on human-robot collaboration" (2023), Zhang proposes a novel approach that integrates human guidance with autonomous robotic navigation to improve precision and efficiency in challenging, uneven terrains. This contribution addresses a critical gap in agricultural automation, where traditional path planning often fails in complex, non-uniform landscapes. With 6 citations to date, his research is gaining traction among scholars in robotics and precision agriculture. Zhang’s work not only enhances operational safety and productivity but also lays groundwork for broader applications in human-robot cooperative systems. His achievements reflect a commitment to bridging human expertise and robotic autonomy, offering practical solutions for sustainable agriculture and forestry management.
Research Focus
Key Achievements
Top Papers
- 1