Peng Zhai
Papers
5
Total Citations
17
H-Index
2
About
Peng Zhai is a leading researcher in robotics and intelligent control systems, with a primary focus on fault-tolerant motion control for quadruped robots and hybrid terrestrial-aerial robotic platforms. His major contributions include pioneering the use of multi-task learning and redundant estimator networks to enable quadruped robots to actively sense and recover from leg failures—such as unexpected joint power loss or locking—without relying on compromised vision systems. This work, published in 2024 and 2025, addresses critical safety and reliability challenges for outdoor exploration robots. Zhai’s research has garnered over 17 citations, with his most-cited paper, "Multi-Task Learning of Active Fault-Tolerant Controller for Leg Failures in Quadruped robots," receiving 10 citations. He also led the design and implementation of "FlyingDog," a novel hybrid robot that combines the maneuverability of a quadrotor drone with the energy efficiency of a quadruped, showcasing his innovative approach to integrating flight and locomotion. Additionally, Zhai has explored deep reinforcement learning for motion simulation of flying quadruped robots and machine vision for welding automation, demonstrating a broad technical range. His work is highly relevant for students and researchers interested in resilient robotic systems, embodied AI, and multi-modal locomotion.
Research Focus
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Top Papers
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