Sheng Miao
Papers
2
Total Citations
23
H-Index
2
About
Sheng Miao is a robotics researcher whose work bridges autonomous navigation and advanced control systems for complex robotic platforms. His primary research areas include humanoid robot autonomy, simultaneous localization and mapping (SLAM), and precision control of parallel robots. Miao’s most cited work, “Camera Recognition and Laser Detection based on EKF-SLAM in the Autonomous Navigation of Humanoid Robot” (2017, 16 citations), addresses a critical challenge in real-world robotics: enabling humanoid robots like NAO to navigate unknown environments by fusing camera-based object recognition with laser detection through an Extended Kalman Filter SLAM framework. This integration allows robots to understand their surroundings and localize themselves simultaneously, a fundamental capability for autonomous operation. In his more recent work, “Fractional-order internal model control algorithm based on the force/position control structure of redundant actuation parallel robot” (2020, 7 citations), Miao tackles the complexity of controlling redundantly actuated parallel robots—systems with more actuators than necessary for a given motion. He proposes a novel force/position hybrid control structure that replaces traditional PID methods with a fractional-order internal model controller, offering superior precision and robustness. This work demonstrates Miao’s ability to push beyond conventional control theory, applying advanced mathematical frameworks to solve practical engineering problems in robotics.
Research Focus
Key Achievements
Top Papers
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