Max Robotics — Global Service Robot Directory + US Certification

About

Xianyu Qi is a robotics researcher whose work sits at the intersection of Simultaneous Localization and Mapping (SLAM), semantic scene understanding, and autonomous robot navigation. His research has made meaningful contributions to the challenge of enabling mobile and service robots to perceive, model, and navigate complex real-world environments with greater intelligence and robustness. Qi's most influential contribution, SO-SLAM (2022, 83 citations), advances object-level SLAM by addressing persistent difficulties such as partial observations and occlusions through scale proportional and symmetrical texture constraints. His earlier DRE-SLAM (2019, 67 citations) tackled the critical limitation of visual SLAM systems that assume static environments, extending their applicability to dynamic real-world settings. Across multiple works, Qi has pioneered the integration of semantic information—using quadric representations, object-semantic grid maps, and topological structures—to move robots beyond purely geometric mapping toward richer, human-friendly scene understanding. Beyond localization and mapping, Qi has explored affective modeling for social robots and semantic navigation frameworks that support socially aware, goal-directed behavior indoors. With over 300 total citations and consistent publication output through 2024, his research portfolio reflects a sustained and impactful effort to bridge low-level spatial perception with high-level semantic reasoning for next-generation autonomous robots.