Max Robotics — Global Service Robot Directory + US Certification

About

Khusniddin Fozilov is at the forefront of advancing autonomous robotic systems for minimally invasive surgery, with his work bridging the critical gap between teleoperation and full surgical autonomy. His research centers on developing intelligent frameworks that enable surgical robots to reason, plan, and adapt during complex procedures. Fozilov’s most impactful contribution, a concurrent framework for constrained inverse kinematics of surgical robots (27 citations), directly addresses the core challenge of enabling precise, safe motion in the confined anatomical spaces typical of minimally invasive procedures. He further advanced the field with a hybrid architecture combining task-motion planning with dynamic behavior trees (12 citations), a novel approach that reduces surgeons’ cognitive load while ensuring robust adaptation during surgery. Beyond the operating room, Fozilov has contributed to visual assistance systems for remote robot control, developing adaptive region-of-interest selection to improve teleoperation efficiency. His work on self-autonomy evaluation using behavior trees lays groundwork for adjustable autonomy in multi-robot teams. Through these contributions, Fozilov is helping to define the next generation of surgical robotics—systems that are not merely tools, but intelligent partners capable of progressively higher levels of autonomous decision-making.