Yuan Yik Kok

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About

Yuan Yik Kok is a robotics researcher whose work focuses on advancing autonomous manipulation for e-commerce and warehouse automation. His primary research areas include robotic grasping, motion planning, and integrated system design for item picking in unstructured environments. Kok’s major contributions center on developing robust, strategy-based approaches to automate item picking from shelves—a pressing challenge in modern logistics. His most cited work, “A Robust Robot Design for Item Picking” (2018, 30 citations), details a comprehensive system built for the Amazon Robotics Challenge, integrating grasping, vision, and motion planning to achieve reliable performance under real-world constraints. This work builds on his earlier paper, “Strategy-based robotic item picking from shelves” (2016, 16 citations), which introduced an effective planning framework to handle the massive variety of items, tight spatial constraints, and location uncertainty typical of e-commerce warehouses. Kok’s research has directly addressed the gap between laboratory robotics and practical deployment, demonstrating how systematic design and strategic planning can yield stable, efficient picking systems. His achievements include successful participation in competitive robotics challenges, where his team’s robot showcased robust performance. For students and researchers, Kok’s work offers valuable insights into the engineering trade-offs and algorithmic innovations needed to bring robotic automation to real-world logistics.