4 papers
Learning to Solve Mixed-Integer Nonlinear Programming with Neural Networks and Sequential Quadratic Programming Refinement
Viet-Anh Le, Rahul Mangharam
We propose a learning-to-optimize framework for solving parametric mixed-integer nonlinear programs arising in model predictive control and trajectory optimization. The proposed me…
Toward Single-Step MPPI via Differentiable Predictive Control
Viet-Anh Le, Renukanandan Tumu, Rahul Mangharam
Model predictive path integral (MPPI) is a sampling-based method for solving complex model predictive control (MPC) problems, but its real-time implementation is challenged by comp…
Nonplanar Model Predictive Control for Autonomous Vehicles with Recursive Sparse Gaussian Process Dynamics
Ahmad Amine, Kabir Puri, Viet-Anh Le +1
This paper proposes a nonplanar model predictive control (MPC) framework for autonomous vehicles operating on nonplanar terrain. To approximate complex vehicle dynamics in such env…
A Hybrid Learning-to-Optimize Framework for Mixed-Integer Quadratic Programming
Viet-Anh Le, Mu Xie, Rahul Mangharam
In this paper, we propose a learning-to-optimize (L2O) framework to accelerate solving parametric mixed-integer quadratic programming (MIQP) problems, with a particular focus on mi…