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About

Yongxiang Dong is a leading researcher in agricultural and dual-arm robotics, focusing on autonomous harvesting and intelligent manipulation. His work addresses critical labor shortages in agriculture through the development of specialized robots for fruit and vegetable picking. Dong’s major contributions include pioneering adaptive end-effector pose control for tomato harvesting robots (33 citations), which optimizes reachable poses within a manipulator’s non-dexterous workspace, and designing an automatic sweet pepper harvesting robot (10 citations) that tackles commercial deployment challenges. He has also advanced cooperative control for dual-arm systems using improved dynamic movement primitives (8 citations), enabling precise manipulation of uncertain objects, and developed efficient grasping and pushing strategies for dense stacking scenarios (2 citations) via mask functions and pixel overlap rates. His research integrates vision systems and learning-based methods to enhance robot dexterity and reliability in complex environments. With a growing citation impact, Dong’s work is pivotal for the future of agricultural automation and robotic manipulation, offering practical solutions to real-world harvesting and object handling challenges.