Papers
1
Total Citations
17
H-Index
1
About
Di Yang is a roboticist specializing in simultaneous localization and mapping (SLAM), with a particular focus on active perception and three-dimensional (3D) environments. Their most cited work, "On-line 3D active pose-graph SLAM based on key poses using graph topology and sub-maps" (2019, 17 citations), introduces a novel framework that enables robots to autonomously plan trajectories for loop-closure by revisiting key poses. This approach leverages graph topology and sub-maps to optimize navigation and mapping in complex 3D spaces, addressing a critical challenge in autonomous robotics: balancing exploration with map accuracy. Yang’s contributions advance the field of active SLAM by providing a method for robots to intelligently decide where to move next, reducing uncertainty and improving long-term localization. Their work is particularly relevant for applications in search-and-rescue, autonomous inspection, and planetary exploration, where reliable 3D mapping is essential. By integrating graph-based reasoning with real-time decision-making, Yang has helped bridge the gap between theoretical SLAM algorithms and practical robotic deployment.
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