Papers
2
Total Citations
4
H-Index
2
About
Mingze Xi is pioneering the intersection of field robotics and large foundation models, with a focus on enabling autonomous systems to understand and act within complex, unstructured environments. His research centers on event-triggered robotic investigation, multi-modal 3D scene representation, and semantic reasoning for task planning. In his 2024 work, "Demonstrating Event-Triggered Investigation and Sample Collection for Human Scientists using Field Robots and Large Foundation Models," Xi showcased how robots can autonomously identify scientific events and collect samples, bridging the gap between human intent and robotic execution. His 2025 paper, "Queryable 3D Scene Representation," introduces a multi-modal framework that fuses geometric accuracy with semantic understanding, allowing robots to interpret high-level human commands and plan intricate tasks. Though early in his career, Xi’s contributions are already gaining traction, with each paper cited twice, signaling growing interest from the robotics and AI communities. His work promises to revolutionize autonomous scientific exploration and human-robot collaboration in dynamic, real-world settings.
Research Focus
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Top Papers
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