Yongping Shi

Anhui University of Science and Technology, Hefei University of Technology

Papers

Total Citations

H-Index

About

Yongping Shi is a robotics researcher whose work centers on motion control, inverse kinematics, and human–robot collaboration. Their most significant contribution is the design and implementation of a distributed architecture for the CMOR motion control system (2022, 16 citations), which has become a foundational reference in the field. Building on this, Shi developed the Dynamic Factor Particle Swarm Optimization (DFPSO) algorithm, which uses a pose decomposition strategy to solve inverse kinematics for CMOR (2023, 5 citations), demonstrating a novel approach to optimizing robotic motion. In their most recent work (2025, 3 citations), Shi addresses a critical challenge in collaborative robotics: estimating joint external torque without relying on expensive torque sensors. Their proposed model, based on a BP neural network, offers a cost-effective alternative to the classic first-order momentum observer, enhancing safety in human–robot interaction. This trajectory—from system architecture to optimization algorithms and sensor-free estimation—positions Shi as a researcher advancing both the theoretical and practical aspects of lightweight, collaborative robots.