Zhe Qiu

Ritsumeikan University, Robotics Research (United States)

Papers

Total Citations

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About

Zhe Qiu is a robotics researcher focused on tackling labor shortages in Japan’s food and agricultural industries through intelligent automation. Their core research spans robotic end-effector design, soft robotics, and deep learning for food handling. Qiu’s most cited work, “An Evaluation System of Robotic End-Effectors for Food Handling” (2023, 18 citations), systematically assesses gripper performance across diverse food types, addressing a critical gap in industrial robotics. They further advanced the field with a ROS 2-based pick-and-place system for granular materials (2022, 8 citations), solving the complex challenge of grasping variable quantities by volume. Qiu also contributed to soft robotics with an empirical model of bellows actuators (2024, 6 citations), leveraging flexibility for unstructured environments like food factories. To support deep learning applications, they developed a synthetic dataset for food sorting (2024, 4 citations), reducing the labor-intensive process of manual data creation. Together, Qiu’s work bridges hardware design, control systems, and data generation, offering scalable solutions for automating food handling in aging societies.