About

Alexandre Kruszewski is a prominent researcher whose work spans two interconnected domains: soft robotics control and networked control systems. He is best known for pioneering the application of Finite Element Method (FEM)-based modeling to achieve real-time kinematics and closed-loop control of soft and continuum manipulators, a contribution that has fundamentally shaped how researchers approach the inherently nonlinear, compliant behavior of these systems. His 2018 paper on FEM-based kinematics alone has garnered 127 citations, reflecting its foundational influence in the field. Kruszewski's research consistently addresses the computational challenges of FEM, developing reduced-order models and state observers that make dynamic control of soft robots practically feasible in real-time environments. His bio-inspired deformable spine manipulator and visual servoing strategies further demonstrate his ability to bridge theoretical modeling with experimental implementation. Notably, his interdisciplinary reach extends to biomedical robotics, including robot-assisted in vivo mass spectrometry imaging. Earlier in his career, Kruszewski made significant contributions to networked control systems, proposing switched-system frameworks for exponential stabilization over communication networks. With multiple papers exceeding 50 citations and a cumulative body of work influencing both robotics and control engineering communities, he stands as a leading voice in model-based soft robot control design.

Research Focus

Key Achievements

15
H-Index
25
Papers
814
Total Citations
33
Avg Citations/Paper
🏆 Most Cited Paper
Finite Element Method-Based Kinematics and Closed-Loop Control of Soft, Continuum Manipulators
127 citations · 2018
📈 Most Prolific Year: 2020 (4 Papers)
🤝 Key Collaborators: 35
🏛 Institutions: Centre National de la Recherche Scientifique, École Centrale de Lille, Centre de Recherche en Informatique, Laboratoire d'Automatique, Génie Informatique et Signal, Institut national de recherche en sciences et technologies du numérique, Université de Lille

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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