Max Robotics — Global Service Robot Directory + US Certification

About

Long Cui is a robotics researcher whose work spans robot learning from demonstration, swarm robotics, continuum and soft robotics, and autonomous manipulation. His most significant contribution lies in advancing robot assembly skills through learning-based approaches: his 2020 paper on peg-in-hole assembly using Cartesian Dynamic Movement Primitives (DMPs) with hybrid force/position feedback has garnered 26 citations, establishing him as a notable voice in compliant robot manipulation. By drawing on human demonstration to enable robots to perform precise industrial assembly tasks, Cui bridges machine learning and practical automation challenges. Beyond assembly tasks, Cui has explored diverse frontiers in robotics. His work on the Morphobot swarm platform investigates emergent collective behaviors, while his modeling of notched continuum snake-like robots addresses minimally invasive surgical applications. His insect-inspired passive wing collision recovery research reflects a growing interest in bio-inspired micro-robotics. Earlier contributions to trajectory generation through motion modularity and motion description languages demonstrate a consistent commitment to foundational robot control problems. With a publication record spanning manipulation, medical robotics, swarm systems, and bio-inspired design, Cui exemplifies a versatile and interdisciplinary approach to modern robotics research, making his work highly relevant for students exploring autonomous systems and human-robot interaction.