Mario Zanon

About

Mario Zanon is a leading researcher in model predictive control (MPC) and its application to robotic locomotion and autonomous systems. His work focuses on developing advanced control strategies that enable robots to navigate complex, unstructured environments with agility and stability. Zanon is best known for pioneering MPC schemes that eliminate the need for stabilizing constraints or costs, a breakthrough demonstrated in his highly cited 2015 paper on nonholonomic mobile robots (117 citations). This work, along with his contributions to differential drive robot regulation (30 citations), established a rigorous theoretical framework for asymptotic stability in nonlinear systems. More recently, Zanon has made significant strides in legged robotics, developing mobility-enhanced and environment-adaptive NMPC for dynamic locomotion on rough terrain (46 citations in 2021). His research bridges the gap between theoretical control theory and real-world deployment, with experimental validation on legged platforms. Zanon’s work is supported by major European and Canadian research grants, and his contributions are essential reading for anyone interested in the intersection of optimization, control, and robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Model Predictive Control of Nonholonomic Mobile Robots Without Stabilizing Constraints and Costs

   117 citations · 2015
2. 2
   Model Predictive Control With Environment Adaptation for Legged Locomotion

   46 citations · 2021
3. 3
   Regulation of Differential Drive Robots using Continuous Time MPC without Stabilizing Constraints or Costs**M.W. Mehrez, G.K.I. Mann, and R.G. Gosine are supported by Natural Sciences and Engineering Research Council of Canada (NSERC), the Research and Development Corporation (RDC), CCORE J.I. Clark Chair, and Memorial University of Newfoundland. M. Zanon and M. Diehl are supported by Research Council KUL: PFV/10/002 Optimization in Engineering Center OPTEC, GOA/10/09 MaNet and GOA/10/11 Global real- time optimal control of autonomous robots and mechatronic systems, KULBOF OT/10/035. Flemish Government: FWO: PhD/postdoc grants, FWO KAN2013 1.5.189.13, FWO-G.0930.13; IWT: PhD Grants, projects: Eurostars SMART; Belgian Federal Science Policy Office: IUAP P7 (DYSCO, Dynamical systems, control and optimization, 2012-2017); EU: FP7-SADCO (MC ITN-264735), FP7-TEMPO (MC ITN-607957), ERC HIGHWIND (259 166).

   30 citations · 2015
4. 4
   Mobility-enhanced MPC for Legged Locomotion on Rough Terrain.

   4 citations · 2021

Key Collaborators

Contact & Links