Papers
1
Total Citations
2
H-Index
1
About
Yutao Chen’s research centers on robotics and computer vision, with a particular focus on 3D perception for autonomous manipulation in challenging environments. His most notable contribution is a novel target measurement method based on sparse disparity, developed for live power lines maintaining robots. This work, published in 2020, leverages binocular stereo vision theory to enable robots to accurately perceive their surroundings and reconstruct three-dimensional scenes, even under the constraints of high-voltage, outdoor settings. By improving the reliability of 3D reconstruction, Chen’s method directly enhances the safety and precision of robotic maintenance tasks on live power lines—a critical application for modern energy infrastructure. Though his citation count is currently modest, the practical significance of his work in field robotics and its potential for future impact in autonomous inspection systems is clear. Chen’s approach represents a meaningful step toward making manipulator robots more perceptive and autonomous in real-world, high-stakes environments.
Research Focus
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Top Papers
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