Papers
5
Total Citations
151
H-Index
4
About
Chengjie Jiang is a researcher advancing the fields of agricultural robotics and intelligent perception, with a focus on computer vision and autonomous navigation. His most impactful work, "DSW-YOLO: A detection method for ground-planted strawberry fruits under different occlusion levels" (2023, 107 citations), presents a novel deep learning approach that significantly improves fruit detection accuracy in complex, occluded environments—a critical challenge for harvesting robots. Building on this, his 2024 study on real-time detection and instance segmentation of strawberries in unstructured environments further refines automated fruit recognition. In robotics, Jiang addresses dynamic obstacle avoidance by integrating an improved A-star algorithm with the Dynamic Window Approach (DWA), reducing path search time and enhancing smoothness for mobile robots. He also explores bio-inspired materials, contributing to the development of semi-liquid metal-based electronic skin with high permeability and adhesion, mimicking spider web properties. With over 150 total citations, Jiang’s work bridges agricultural automation and robotics, offering practical solutions for unstructured environments. His achievements demonstrate a commitment to creating robust, real-time systems that advance both precision agriculture and autonomous navigation technologies.
Research Focus
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