Yingbo Wang

Beijing Jiaotong University, Shandong University

Papers

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About

Yingbo Wang is a researcher at the forefront of autonomous systems and robotics, with key contributions spanning 3D perception, simultaneous localization and mapping (SLAM), and bio-inspired underwater robotics. Wang’s work in autonomous driving is exemplified by a tracking-by-detection framework for 3D multiple object tracking, which enhances real-time perception in dynamic environments. Addressing the persistent challenge of robust mapping in complex settings, Wang developed an efficient and accurate 3D SLAM method using LiDAR, achieving high precision despite moving obstacles—a critical advance for self-driving cars and mobile robots. Each of these works has garnered 2 citations, reflecting their emerging influence. In a notable interdisciplinary leap, Wang also explores soft robotics, modeling the hydrodynamic and motion characteristics of flexible, asymmetric-swimming limbs for underwater robots. This work demonstrates a unique ability to bridge mechanical design and fluid dynamics, opening new possibilities for agile, soft-bodied underwater exploration. Wang’s research portfolio, though early in its citation trajectory, showcases a versatile and impactful approach to solving real-world challenges in perception, mapping, and bio-inspired locomotion, promising significant future contributions to both autonomous and robotic systems.