Peng Cheng Cao

Guangxi University of Science and Technology

Papers

Total Citations

H-Index

About

Peng Cheng Cao is a leading researcher in agricultural robotics and computer vision, with a primary focus on intelligent fruit harvesting systems. His most cited work, "Research on Spatial Positioning System of Fruits to be Picked in Field Based on Binocular Vision and SSD Model" (2021, 24 citations), addresses a critical challenge in precision agriculture: accurate fruit recognition and spatial localization for autonomous picking robots. Cao pioneered an improved Single Shot Multi-Box Detector (SSD) model that integrates color and morphological fruit characteristics, significantly enhancing detection accuracy in complex field environments. This contribution directly advances the practical deployment of agricultural robots by solving the long-standing problem of reliable fruit identification under variable lighting and occlusion conditions. His research bridges deep learning with real-world agricultural applications, demonstrating how computer vision can transform labor-intensive harvesting processes. Cao's work has been recognized for its potential to increase agricultural efficiency and reduce crop waste, positioning him as an innovator at the intersection of robotics, artificial intelligence, and sustainable farming. His findings continue to influence subsequent studies on autonomous picking systems and field-based object detection.