Gianni Lunardi — accepted AI-conference papers

2025

Parallel-Constraint Model Predictive Control: Exploiting Parallel Computation for Improving Safety

Elias Fontanari, Gianni Lunardi, Matteo Saveriano, Andrea Del Prete

ICRA 2025

Ensuring constraint satisfaction is a key requirement for safety-critical systems, which include most robotic platforms. For example, constraints can be used for modeling joint position/velocity/torque limits and collision avoidance. Constrained systems are often controlled using Model Predictive Co

Cited by 1 Source ↗Scholar ↗

2024

Receding-Constraint Model Predictive Control using a Learned Approximate Control-Invariant Set

Gianni Lunardi, Asia La Rocca, Matteo Saveriano, Andrea Del Prete

ICRA 2024poster

In recent years, advanced model-based and data-driven control methods are unlocking the potential of complex robotics systems, and we can expect this trend to continue at an exponential rate in the near future. However, ensuring safety with these advanced control methods remains a challenge. A well-…

Cited by 2 Source ↗code ↗Scholar ↗