About

Philippe Chevrel is a leading figure in the modeling, simulation, and control of advanced robotic and vehicular systems, with a particular focus on urban mobility and autonomous navigation. His pioneering work on narrow tilting cars—vehicles designed to alleviate traffic congestion, pollution, and parking challenges—has been foundational, as demonstrated by his most-cited paper, "Modeling and Simulating a Narrow Tilting Car Using Robotics Formalism" (2014, 19 citations). By applying robotics formalism, including geometric and dynamic models with closed kinematic chains, Chevrel has provided a unique framework for developing these compact, efficient urban vehicles. His research extends to two-wheeled vehicles with suspensions and cable-driven parallel robots, addressing elasticity and sagging in dynamic simulations. In autonomous mobile robotics, Chevrel has made significant contributions to real-time motion planning, notably in "Real-time motion planning for an autonomous mobile robot with wheel-ground adhesion constraint" (2023, 5 citations), where he integrates actuator limits and traction constraints to generate collision-free, time-optimal trajectories. He has also advanced control theory, tackling stochastic LQ control and asymptotic tracking over lossy communication channels. With a career spanning over a decade, Chevrel’s work is essential reading for students and researchers in robotics, vehicle dynamics, and control systems, offering practical solutions for next-generation transportation and automation.

Research Focus

Key Achievements

4
H-Index
7
Papers
44
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Modeling and Simulating a Narrow Tilting Car Using Robotics Formalism
19 citations · 2014
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: École Nationale Supérieure des Mines de Paris, Laboratoire des Sciences du Numérique de Nantes, École Centrale de Nantes, Institut Mines-Télécom

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago