Papers
5
Total Citations
60
H-Index
4
About
Yichao Mao is a robotics researcher whose work bridges the gap between human-like dexterity and machine precision, focusing on motion retargeting, adaptive control, and human-robot interaction. His most impactful contribution is the development of a Dynamic Movement Primitive (DMP)-based framework for transferring complex dual-arm sign language motions from humans to robots, a breakthrough that enables service robots to perform coordinated, expressive gestures with both arms and hands (23 citations). Mao also advanced legged robotics through adaptive torque and position control for Series Elastic Actuators (SEAs), achieving natural, compliant locomotion inspired by biological systems (21 citations). His work on visual servoing introduced a novel controller leveraging ABB’s External Guided Motion (EGM) interface, offering unprecedented adaptability to varying feedback frequencies without sacrificing accuracy (7 citations). Additionally, Mao addressed real-world robot robustness by developing adaptive compliance control for bipedal robots, allowing them to maintain posture under unknown payloads and external disturbances (6 citations). Through these contributions, Mao has established himself as a key figure in making robots more capable, adaptable, and human-friendly.
Research Focus
Key Achievements
Top Papers
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- 3Visual Servoing Control Based on EGM Interface of an ABB Robot7 citations · 2018
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