Zicong Xiong

Beijing Academy of Agricultural and Forestry Sciences, Beijing Automation Control Equipment Institute, Guangxi University

Papers

Total Citations

131

H-Index

About

Zicong Xiong is a leading researcher in agricultural robotics, with a focused expertise in robotic harvesting systems for fresh fruit. His work primarily addresses the critical challenge of intelligent fruit perception and manipulation, bridging computer vision and mechanical design to automate complex agricultural tasks. Xiong’s major contributions include pioneering advancements in target visual information acquisition, as detailed in his highly cited 2022 review (51 citations), which systematically analyzed the bottlenecks in guiding robots to accurately perceive fruit in unstructured orchard environments. He further advanced the field by developing MTA-YOLACT, a multitask-aware network for precise fruit bunch identification in cherry tomato harvesting (50 citations), significantly improving detection accuracy under occluded conditions. Demonstrating a holistic approach, his work on dual-manipulator optimal design for apple harvesting (30 citations) introduced a configuration optimization method that maximizes canopy coverage while minimizing mechanical complexity. With over 130 total citations, Xiong’s integrated research—spanning perception algorithms and hardware design—is instrumental in moving robotic harvesting from concept to practical, labor-saving solutions for the global fruit industry.