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About

Runpeng Jiang is an emerging researcher specializing in agricultural robotics, with a particular focus on autonomous navigation, path planning, and motion control for orchard mowing robots. His work addresses the critical challenge of deploying mobile robots in complex, unstructured agricultural environments, where irregular terrain, narrow passages, and unpredictable obstacles pose significant safety and precision concerns. Jiang's most notable contributions include the development of an improved artificial potential field algorithm incorporating elliptic repulsion scope boundary constraints, enabling safer and more adaptive local path planning in orchard settings — a paper that has garnered 12 citations since its 2023 publication. Complementing this, his research on cascaded Model Predictive Control combined with anti-slip drive control tackles the persistent problem of longitudinal wheel slippage, substantially improving path tracking accuracy and autonomous navigation reliability, earning 11 citations. His more recent 2024 work employs safe corridor formulations and quadratic programming to further refine local planning under kinematic constraints. Collectively, Jiang's research represents a systematic effort to bridge the gap between theoretical robotics and real-world agricultural deployment, offering practical algorithmic solutions that enhance the operational safety and efficiency of autonomous orchard machinery — making his work increasingly relevant to the growing field of precision agriculture.