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About

Yanli Du is a robotics researcher whose work centers on the control, localization, and intelligent optimization of reconfigurable modular robots. Her key contributions lie at the intersection of inverse kinematics, simultaneous localization and mapping (SLAM), and decentralized force control. In her most cited work (19 citations), Du introduced an improved particle swarm optimization (IPSO) algorithm with a mutation operator to solve the complex inverse kinematics of reconfigurable modular robots, offering a generalizable analytic method that adapts as joint numbers increase. She further advanced mobile robotics by developing an optimized coverage SLAM algorithm based on an improved particle filter for wireless sensor network (WSN) nodes, enhancing positioning accuracy and environmental mapping. Du also addressed critical challenges in constrained-space manipulation by designing a double closed-loop decentralized force/position controller using a nonlinear joint torque observer, enabling precise end-effector control without requiring joint-mounted torque sensors. Her work demonstrates a sustained focus on overcoming modeling uncertainties and coupling effects in modular robotic systems, contributing practical algorithms for both kinematic and dynamic control.