Liren Yang

Huazhong University of Science and Technology

Papers

Total Citations

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About

Liren Yang is a leading researcher in the field of robotics, with a primary focus on robot dynamics identification, collision detection, and human-robot collaboration. Their work addresses critical challenges in modern industrial settings where robots must operate safely alongside humans in unstructured environments. Yang’s major contributions include the development of a switched momentum dynamics identification method for robot collision detection, which has garnered 11 citations since its 2024 publication. This approach significantly enhances the ability to detect and mitigate robot-human and robot-environment collisions, reducing potential harm in collaborative workspaces. Additionally, Yang introduced a two-stage Bayesian framework for rapid dynamics identification in industrial robots, enabling real-time model updates that are essential for precise model-based control, motion planning, and disturbance estimation. This framework allows robots to adapt flexibly to evolving environments and tasks, marking a notable advancement in adaptive robotics. With a growing citation record and innovative methodologies, Yang is establishing themselves as a key contributor to safer and more intelligent robotic systems, with their work poised to influence both academic research and practical industrial applications.