25 citations · 67 across the 17 of their papers we have counts for
4 papers · 1 filter
Safe multi-agent motion planning under uncertainty for drones using filtered reinforcement learning
Sleiman Safaoui, Abraham P. Vinod, Ankush Chakrabarty +3
We consider the problem of safe multi-agent motion planning for drones in uncertain, cluttered workspaces. For this problem, we present a tractable motion planner that builds upon…
Real-time Mixed-Integer Quadratic Programming for Vehicle Decision Making and Motion Planning
Rien Quirynen, Sleiman Safaoui, Stefano Di Cairano
We develop a real-time feasible mixed-integer programming-based decision making (MIP-DM) system for automated driving. Using a linear vehicle model in a road-aligned coordinate fra…
Robust Parameter Estimation for Hybrid Dynamical Systems
Ryan S. Johnson, Stefano Di Cairano, Ricardo G. Sanfelice
We consider the problem of estimating a vector of unknown constant parameters for a class of hybrid dynamical systems -- that is, systems whose state variables exhibit both continu…
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems
Truong X. Nghiem, Ján Drgoňa, Colin Jones +10
Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathema…