Xiang Dou

Papers

Total Citations

H-Index

About

Xiang Dou is a researcher whose work lies at the intersection of robotics, perception, and intelligent interaction. His primary focus is on enabling robots to actively explore and understand their environment using non-visual cues. In his most cited work, "Active Auditory Exploration for Identifying Object Contents," Dou tackles a fundamental challenge in robotic manipulation: how a robot can determine the contents of a container without opening it. By proposing a framework where robots strategically select actions—such as shaking or tapping—to generate informative sounds, he demonstrates that auditory feedback can be a powerful tool for object recognition. This approach is critical for tasks requiring efficiency and accuracy, such as sorting or retrieving items in cluttered or opaque containers. While early in its citation trajectory, this work represents a novel contribution to embodied AI and active perception. Dou’s research promises to advance the capabilities of service and industrial robots, making them more autonomous and perceptive in real-world scenarios. His efforts highlight the importance of multimodal sensing in the future of intelligent robotics.