Benjie Wu

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About

Benjie Wu is a robotics researcher whose work bridges the gap between human intent and machine autonomy. His primary research areas include sensor fusion for simultaneous localization and mapping (SLAM), human-robot interaction via biosignals, and mobile robot control systems. Wu’s most notable contribution is a novel SLAM system that fuses binocular vision with an inertial measurement unit (IMU), built upon the ORBSLAM2 framework. By initializing the visual and inertial components separately before tightly coupling them, his approach significantly enhances localization accuracy for mobile robots in indoor environments—a critical advancement for autonomous navigation. This work has garnered 5 citations. In parallel, Wu explores non-traditional control interfaces, as demonstrated in his design of a mobile robot control system driven by electromyography (EMG) signals. This research, with 4 citations, enables hands-free remote control by translating muscle activity into command inputs, opening new possibilities for assistive robotics and human-machine collaboration. Through these contributions, Wu is advancing both the precision of autonomous systems and the accessibility of robotic control.