Yi Shao

Papers

Total Citations

H-Index

About

Yi Shao is a rising researcher at the forefront of autonomous construction robotics, specializing in robotic motion planning, mobile manipulation, and imitation learning for structural assembly. His work directly addresses critical bottlenecks in on-site construction automation, particularly the challenge of manipulating heavy, flexible rebar components. Shao’s most-cited paper, “Robotic motion planning for autonomous in-situ construction of building structures” (2025, 9 citations), pioneers algorithms that enable robots to navigate unstructured environments and assemble building components without pre-installed infrastructure. Building on this, his paper “Mobile robotic rebar cage assembly via imitation learning” (2025, 2 citations) introduces a novel framework that combines visual servoing with a mobile manipulator, overcoming the cost and scalability limitations of traditional rail-guided systems. By teaching robots to mimic human assembly strategies, Shao’s work significantly advances the feasibility of fully autonomous rebar cage construction—a long-standing hurdle in the industry. His research has immediate implications for reducing labor costs and improving safety on construction sites. With a focus on practical, scalable solutions, Yi Shao is establishing himself as a key innovator in the intersection of robotics and civil infrastructure.