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About

Tianjiao Liao is a robotics researcher whose work focuses on a critical challenge in legged locomotion: energy efficiency. Liao’s primary research areas include quadrupedal robotics, foothold planning, and trajectory optimization for rough terrain navigation. Their major contributions center on developing strategies to bridge the performance gap between legged and wheeled robots, specifically by reducing the high energy consumption that limits legged robots’ practical deployment in patrol and rescue missions. Liao’s most cited works—including "CNNs based Foothold Selection for Energy-Efficient Quadruped Locomotion over Rough Terrains" and "Energy Efficient Swing Leg Trajectory Planning For Quadruped Robots Walking On Rough Terrain"—each have garnered 15 citations, demonstrating steady impact in the field. A notable achievement is their integrated approach combining optimized stance parameters with posture searching, as presented in their 2020 paper "Optimized Foothold Planning and Posture Searching for Energy-Efficient Quadruped Locomotion over Challenging Terrains." This work systematically addresses the fundamental trade-off between terrain adaptability and operational endurance, offering practical solutions for extending robot mission times in demanding outdoor environments.