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About

Nicola Scianca is a robotics researcher whose work sits at the intersection of humanoid locomotion, motion planning, and safe human-robot interaction. His research has made significant contributions to the field of bipedal gait generation, most notably through the development of the Intrinsically Stable Model Predictive Control (IS-MPC) framework — a real-time approach for generating stable, adaptive walking trajectories for humanoid robots across varied and challenging terrains, including uneven ground and staircase environments. Scianca's work spans the full locomotion spectrum, from walking to running, while addressing critical challenges such as robustness to disturbances, step timing adaptation, and feasibility guarantees in constrained optimization. His 2019 teleoperation framework for the iCub robot (40 citations) demonstrated how humanoids can be deployed in hazardous real-world scenarios, reflecting a broader commitment to practical, safety-conscious robotics. His safety behavior framework further underscores this theme, providing structured protocols for deploying humanoids alongside humans. With a cumulative body of work exceeding 160 citations, Scianca has established himself as a leading voice in humanoid control systems. His most recent contributions continue to push the boundary of closed-loop MPC methods, progressively eliminating reliance on external stabilizers in favor of more principled, integrated control architectures.