Jianming Yao

Guangdong University of Technology, Shenzhen Academy of Robotics

Papers

Total Citations

H-Index

About

Jianming Yao is a robotics researcher whose work focuses on advancing the visual perception and control systems of humanoid and mobile manipulator robots. His key research areas include real-time semantic mapping, whole-body control, and human-robot cooperative manipulation. Yao’s major contributions include developing a real-time polygonal semantic mapping algorithm that enables humanoid robots to navigate complex terrains like staircases, leveraging GPU acceleration for rapid planar extraction. He has also pioneered a framework combining Model Predictive Control (MPC) with whole-body control to enhance coordination between a mobile manipulator’s base and arm during cooperative tasks with humans. With over 8 citations across his most cited works, Yao’s research is gaining traction in the robotics community. His 2024 survey on humanoid robot visual perception provides a comprehensive overview of the field, while his 2025 work on human-robot cooperation addresses critical challenges in intelligent logistics and manufacturing. Yao’s innovative approaches to real-time perception and coordinated control are helping bridge the gap between theoretical robotics and practical, real-world applications.