Xueming Xiao
Papers
11
Total Citations
132
H-Index
6
About
Xueming Xiao is a pioneering roboticist whose research bridges modular robotics, autonomous navigation, and planetary exploration. His work centers on three key areas: reconfigurable modular robots, semantic perception for unstructured environments, and dynamic SLAM (Simultaneous Localization and Mapping). Xiao’s most impactful contribution is **Light4Mars** (2024, 43 citations), a lightweight transformer model enabling semantic segmentation on Mars-like terrains—a critical advancement for planetary rovers. He has also made foundational strides in modular robot reconfiguration, notably through his 2018 paper on optimizing active module distribution (19 citations), which reduces energy and cost in self-folding systems. His **M2CS** dataset (2024, 16 citations) provides a multimodal benchmark for dynamic SLAM, addressing the challenge of moving objects in real-world scenes. Xiao’s innovative **hierarchical deep reinforcement learning** framework (2023, 13 citations) co-optimizes robot morphology and behavior, while his 2020 work on actuation fault tolerance (7 citations) enhances system resilience. His recent **GCNT** model (2025) pioneers morphology-agnostic reinforcement learning, and his terrain-guided optimization approach (2025) adapts modular robots for planetary landforms. With over 130 total citations and a trajectory from fundamental reconfiguration theory to cutting-edge AI for space robotics, Xiao is shaping the future of autonomous, adaptable robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8Towards Peak Torque Minimization for Modular Self-Folding Robots5 citations · 2018
- 9
- 10