Kaiping Wang

Papers

Total Citations

H-Index

About

Kaiping Wang has made impactful contributions to the field of intelligent robotics, with a primary focus on autonomous manipulation and machine vision. Their most-cited work, "Research on Autonomous Grasping of Target Based on Machine Vision" (2021), addresses critical limitations in traditional robot teaching and object-grasping methods. By proposing a control system that integrates visual recognition with feedback-driven robotic arm operations, Wang has advanced the efficiency and adaptability of automated sorting processes—a key challenge in modern manufacturing and logistics. While their citation count remains modest, this foundational research demonstrates a clear trajectory toward practical, vision-guided autonomy in robotics. Wang’s work is particularly relevant for students and researchers exploring the intersection of computer vision and robotic control, offering a scalable framework for real-time, adaptive grasping. Their contributions underscore a commitment to bridging theoretical algorithms with deployable solutions, positioning them as a promising voice in the ongoing evolution of intelligent automation.