Yaheng Wu

About

Yaheng Wu is a leading researcher in autonomous navigation and sensor fusion, with a primary focus on enhancing the precision and reliability of indoor mobile robot positioning. His most influential work, "Data Fusion for Indoor Mobile Robot Positioning Based on Tightly Coupled INS/UWB" (2017, 63 citations), introduces a groundbreaking approach that tightly integrates Ultra Wide Band (UWB) wireless radio with an Inertial Navigation System (INS). This method directly addresses the critical challenge of accumulated error in low-cost Micro-Electromechanical Systems (MEMS) INS, enabling robust real-time tracking in GPS-denied environments. By fusing complementary sensor data, Wu’s framework significantly improves localization accuracy for mobile robots, making it a foundational reference for researchers in robotics, autonomous systems, and indoor positioning. His contributions are particularly vital for applications in warehouse automation, search-and-rescue, and smart infrastructure, where reliable navigation is essential. Wu’s work stands out for its practical impact, offering a scalable solution that balances cost and performance, and continues to inspire advancements in tightly coupled sensor fusion for dynamic, indoor settings.

Research Focus

Key Achievements

Top Papers

1. 1
   Data Fusion for Indoor Mobile Robot Positioning Based on Tightly Coupled INS/UWB

   63 citations · 2017

Key Collaborators

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