Joseph Cenerini
Papers
2
Total Citations
66
H-Index
2
About
Joseph Cenerini is a leading researcher in the field of robotics and control systems, with a primary focus on model predictive control (MPC) for autonomous mobile robots. His work has significantly advanced the practical deployment of MPC by eliminating the need for computationally expensive terminal constraints and costs, making real-time control more efficient and accessible. In his highly influential 2020 paper, "Model Predictive Control without terminal constraints or costs for holonomic mobile robots," which has garnered 41 citations, Cenerini demonstrated that stable, high-performance control can be achieved with simplified formulations. He extended this framework in his 2022 work on model predictive path following control, cited 25 times, further broadening the applicability to path-tracking tasks. These contributions have direct implications for autonomous vehicles, warehouse robotics, and industrial automation, where computational efficiency is critical. Cenerini’s innovative approach has been recognized as a key step toward bridging theoretical MPC with practical, resource-constrained robotic systems, establishing him as a rising authority in control theory and mobile robotics.
Research Focus
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Top Papers
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