Max Robotics — Global Service Robot Directory + US Certification

About

Jay Ryan Roldan’s research lies at the intersection of human-robot interaction, wearable robotics, and surgical automation, with a focus on making robotic systems more intuitive and transparent for human operators. His major contributions center on control algorithms for upper limb exoskeletons, where he pioneered the integration of admittance control with arm redundancy resolution to maximize transparency between human and machine. His 2012 paper on admittance control (22 citations) demonstrates how this synergy reduces energy exchange, enabling exoskeletons to feel like natural extensions of the body. Roldan further advanced this work by developing a viscoelastic model for redundancy resolution via the swivel angle, providing a framework for more fluid, biomimetic control in 7-DOF systems. More recently, he has applied his expertise to constrained surgical environments, designing a pose planner for suture looping tasks (2022). This work showcases his ability to translate principles of human arm modeling into practical, high-stakes applications. With a career spanning foundational exoskeleton control to cutting-edge surgical robotics, Roldan’s research continues to shape how robots collaborate with humans in both rehabilitation and operating rooms.