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Xuesong Shao is a leading researcher in quadruped robotics, specializing in autonomous locomotion, motion planning, and adaptive control for unstructured environments. His work addresses the fundamental challenge of enabling legged robots to navigate complex terrains with minimal prior knowledge. Shao’s most influential contribution, "Obstacle crossing with stereo vision for a quadruped robot" (2012, 17 citations), pioneered the integration of stereo vision with locomotion control, allowing robots to perceive and stride over obstacles autonomously. He further advanced the field with "Trajectory planning and posture adjustment of a quadruped robot for obstacle striding" (2011, 11 citations), introducing a mixed parabola method for smooth, constraint-aware path planning. His research on center-of-gravity adjustment for stable walking (2013, 6 citations) and compliant control on complicated terrains (2014, 5 citations) has been instrumental in improving robot stability and adaptability. Shao also contributed to industrial automation, developing a robotic system with mobile manipulators and vision positioning for electric energy meter detection (2015, 4 citations). His work on inverse dynamics control strategies (2012, 3 citations) offers computationally efficient solutions for compliant locomotion. With a cumulative impact of over 50 citations, Shao’s research continues to shape the future of legged robotics, bridging perception, planning, and control for real-world applications.