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About

Vincenzo Petrone is a robotics researcher whose work centers on the intersection of optimal motion planning, force control, and human-robot interaction. His primary research areas include time-optimal trajectory planning for robots interacting with physical environments, dynamic modeling of industrial manipulators, and the integration of artificial intelligence methods into force-controlled manufacturing tasks. Petrone’s major contributions include developing novel approaches for trajectory optimization that account for wrenches exerted during end-effector contact—a critical advancement for tasks where environmental dynamics are unknown or difficult to model. His most cited work, “Time-Optimal Trajectory Planning With Interaction With the Environment” (2022, 18 citations), addresses this gap directly. He has also made significant strides in dynamic modeling, as demonstrated by his work on the UR10 robot (2025, 8 citations), which employs a triple-stage identification approach for accurate coefficient estimation. Petrone’s research on optimized residual action for interaction control (2023, 4 citations) and actor-critic model predictive force controllers (2023, 2 citations) showcases his commitment to combining classical control theory with modern AI techniques. His work is particularly relevant for industrial applications requiring compliant yet precise force tracking, positioning him as a rising figure in advanced robotic manipulation.