Max Robotics — Global Service Robot Directory + US Certification

About

Roy Lin is a leading researcher in robot manipulation, with a focus on deformable objects and large-scale data-driven robotics. His most impactful work includes the creation of **DROID**, a landmark dataset for in-the-wild robot manipulation that has already garnered over 100 citations since its 2024 release. This dataset addresses a critical bottleneck in robotics—the lack of diverse, real-world training data—by providing a large-scale collection of manipulation trajectories across varied environments, paving the way for more robust and generalizable robotic policies. Lin also tackles the challenging domain of deformable object manipulation. His work on **bagging** introduces an interactive perception method to singulate layers of fabric or plastic, enabling robots to open bags or arrange garments using only visual feedback and standard grippers—a significant step toward automating tasks in homes and industries like garment manufacturing. Additionally, his research on **deformable gasket assembly** demonstrates high-precision, long-horizon manipulation for sealing surfaces in manufacturing, showcasing practical industrial impact. Lin’s contributions are shaping the future of robot learning, bridging the gap between controlled lab settings and the unstructured real world.