Xuming He

Papers

Total Citations

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About

Xuming He is a leading researcher at the intersection of robotics, artificial intelligence, and bio-inspired engineering, with a primary focus on advancing autonomous systems in complex, unstructured environments. His work is particularly distinguished by pioneering contributions to underwater robotics, where he addresses the fundamental challenge of training intelligent control policies for bionic fish-like robots. He developed **FishGym**, a high-performance physics-based simulation framework that has become a cornerstone for underwater robot learning, enabling researchers to overcome the critical bottleneck of scarce real-world training data. This work, already garnering **22 citations** since 2022, provides a scalable platform for developing and testing complex behaviors. Beyond underwater systems, He has made significant strides in terrestrial autonomy, notably with his work on **"Learning Autonomous Exploration and Mapping with Semantic Vision"** (11 citations), which tackles the classic robotics problem of enabling a mobile robot to intelligently explore and map unknown environments using visual inputs. His recent research on learning-based control for fish-like robots in altered background flows (2023) further demonstrates his commitment to pushing the boundaries of robot performance in dynamic, real-world fluid fields, showcasing a unique blend of theoretical rigor and practical application.