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About

Farid Edrisi is a roboticist whose research centers on the control, estimation, and adaptive behavior of robotic systems, with a particular focus on legged locomotion and manipulator dynamics. His most cited work, “Estimation of external forces acting on the legs of a quadruped robot using two nonlinear disturbance observers” (2016, 18 citations), introduces a sensor-less method for estimating environmental forces on quadruped legs, leveraging nonlinear disturbance observers to enhance robot stability without additional hardware. Edrisi further advanced quadruped control in “Modifying the attitude of quadruped robot body against disturbances via data fusion” (2016, 7 citations), where he fused IMU and magnetometer data to correct body orientation under external perturbations. His contributions extend to manipulator systems, as seen in “Estimation of decentralized unknown dynamics for a 2DOF manipulator using a time varying extended state observer” (2016, 5 citations), which simplifies controller design by estimating uncertain dynamics. More recently, his work “Adaptive Controllers and Digital Twin for Self-Adaptive Robotic Manipulators” (2023, 11 citations) explores how digital twins and adaptive control can enable robots to maintain performance in unstructured environments. Edrisi’s research is foundational for building more resilient, self-aware robots capable of operating safely and efficiently in real-world settings.