Weitao Xi

University of Michigan–Ann Arbor, Tencent (China)

Papers

Total Citations

159

H-Index

About

Weitao Xi is a robotics researcher whose work spans legged locomotion, trajectory optimization, and dexterous manipulation. His most influential contributions lie in the study of economical gait selection for legged robots, drawing inspiration from the natural world, where humans and animals instinctively switch gaits — walking, trotting, running — to minimize energy expenditure. His 2015 paper, "Selecting Gaits for Economical Locomotion of Legged Robots," has garnered 104 citations, establishing him as a notable voice in biomechanically inspired robotics. Complementing this, his 2014 work on optimal gaits and motions demonstrated the power of trajectory optimization with unspecified contact sequences, earning 43 citations and offering a principled computational framework for discovering efficient robot movements. Beyond locomotion, Xi has ventured into the challenging frontier of dexterous in-hand manipulation. His 2019 research on learning to solve a Rubik's Cube with a multi-fingered robotic hand tackles one of robotics' most demanding tasks — sequential, multi-step manipulation of a complex object. Together, these contributions reflect a research trajectory that bridges classical mechanics-based robot control with modern machine learning approaches, making Xi a researcher of broad and growing relevance to the robotics community.