Qihao Peng

Papers

Total Citations

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About

Qihao Peng is a robotics researcher whose work centers on visual Simultaneous Localization and Mapping (SLAM), with a particular focus on solving one of the field's most persistent challenges: enabling robust robot navigation in weakly textured environments. Traditional visual SLAM systems struggle in scenes with minimal surface detail — such as plain walls, floors, or featureless corridors — and Peng's research directly confronts this limitation. His signature contribution, the RWT-SLAM system (Robust Visual SLAM for Weak-Textured Environments), represents an evolving line of work developed across multiple iterations from 2022 to 2024, demonstrating a sustained commitment to refining and advancing the approach. By modifying conventional SLAM pipelines to handle the scarcity of reliable visual features, Peng's system offers a meaningful step forward for intelligent robots operating in real-world, unstructured settings. His papers have collectively accumulated over 17 citations, reflecting growing recognition within the robotics and computer vision communities. For students and researchers working on autonomous navigation, robot perception, or SLAM algorithms, Peng's work offers both practical solutions and a compelling research trajectory worth following closely.