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About

Magnus Hanses is a robotics researcher focused on advancing human-robot interaction and medical robotics, particularly in force-controlled manipulation and robot-assisted surgery. His work bridges the gap between simulation and real-world application, addressing critical challenges in precision, safety, and ergonomics. Hanses’ most cited paper, “Performance Indicator for Benchmarking Force-Controlled Robots” (2018, 13 citations), established a framework for evaluating robots in sensitive assembly tasks, a cornerstone for industrial and surgical applications. He has made significant contributions to robotic ultrasound imaging by integrating haptic force feedback for real-time control (2022, 7 citations), enhancing both accuracy and operator comfort. His research on hand-guiding robots along predefined paths under hard joint constraints (2016, 7 citations) directly supports high-precision tasks like robot-assisted surgery, while his work on nonparametric calibration (2017, 4 citations) improves absolute accuracy in lightweight robots. Hanses has also explored risk assessment for spine interventions, including radiofrequency ablations (2019, 4 citations), and tackled sim-to-real transfer challenges in reinforcement learning (2024, 5 citations). With over 40 total citations, his interdisciplinary approach—combining force control, calibration, and medical robotics—positions him as a rising expert in safe, precise robotic systems for healthcare and industry.