Max Robotics — Global Service Robot Directory + US Certification

About

Letian Fu is a robotics researcher whose work sits at the intersection of manipulation, perception, and autonomous decision-making. His key research areas include industrial insertion, mechanical search on shelves, and robot learning from sensorimotor data. Fu’s major contributions include developing safe self-supervised learning methods for visuo-tactile feedback policies, enabling robots to perform high-precision industrial insertion tasks without damaging parts—a problem that has long challenged real-world deployment. He also introduced the novel “Bluction” tool for mechanical search on shelves, which efficiently stacks and destacks objects to improve accessibility in cluttered environments. His work on LEGS (Learning Efficient Grasp Sets) advances exploratory grasping for adversarial objects, while Lifelong LERF demonstrates how mobile robots can jointly optimize language and geometric representations for long-term inventory monitoring. With papers accumulating over 60 citations, Fu’s research is notable for its focus on practical, real-world applications—from factories to homes—and for integrating tactile sensing, self-supervised learning, and generative design. His 2025 work on Blox-Net, which uses vision-language models and physics simulation for generative design-for-robot-assembly, hints at a future where robots can autonomously generate and assemble complex structures from natural language instructions.