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About

Filippo M. Smaldone is a robotics researcher whose work centers on motion planning, locomotion control, and stability for humanoid and mobile robots. He is best known for his contributions to Model Predictive Control (MPC)-based frameworks for humanoid gait generation, particularly his development and continued refinement of the Intrinsically Stable MPC (IS-MPC) method — a real-time approach that generates stable walking and running gaits while closely tracking predefined footstep plans. His research tackles critical challenges in robust locomotion, including disturbance rejection, step timing adaptation, and feasibility guarantees under both persistent and impulsive perturbations, as reflected in papers such as "ZMP Constraint Restriction for Robust Gait Generation in Humanoids" (2020) and "Feasibility-Driven Step Timing Adaptation" (2021). His 2022 extension of this framework to 3D running represents a notable milestone in bridging walking and dynamic running for full-sized humanoids. Beyond bipedal locomotion, Smaldone has also addressed whole-body control for Wheeled Inverted Pendulum robots. With a growing body of cited work — including his most-cited paper accumulating 18 citations — his research is gaining recognition as a meaningful contribution to the field of legged robot locomotion and control.