Chengkun Chen

Guiyang College of Traditional Chinese Medicine, Northwest A&F University, North West Agriculture and Forestry University

Papers

Total Citations

196

H-Index

About

Chengkun Chen is a leading researcher in agricultural robotics, with a focused expertise in robotic fruit harvesting systems, particularly for apples. His work centers on the critical challenge of designing robotic end-effectors and picking strategies that balance high efficiency with minimal mechanical damage to delicate fruit. Chen’s major contributions include the development and validation of optimized picking patterns for robotic apple harvesting, demonstrated through a combination of experimental trials and sophisticated simulation analyses. His most influential work, an experimental and simulation analysis of optimum picking patterns (74 citations), provides foundational insights into the kinematics of fruit detachment. This was followed by the design and evaluation of a complete robotic harvester using those patterns (70 citations), showcasing a direct pathway from theory to application. Further deepening the field, he investigated the dynamic behavior of the apple branch-stem-fruit model (46 citations), crucial for predictive control. Chen also pioneered a method to quantify fruit damage using a “damage factor,” enabling precise assessment of flexible end-effector performance. With over 190 total citations, his research is pivotal for advancing gentle, high-throughput robotic harvesting.