activity
20132024
most citedDistributed Model Predictive Control for Heterogeneous Vehicle Platoons under Unidirectional Topologies

593 citations · 845 across the 62 of their papers we have counts for

collaborators

83 papers

cs.RO2024

A Sequential Quadratic Programming Approach to the Solution of Open-Loop Generalized Nash Equilibria for Autonomous Racing

Edward L. Zhu, Francesco Borrelli

Dynamic games can be an effective approach for modeling interactive behavior between multiple competitive agents in autonomous racing and they provide a theoretical framework for s…

cs.RO2023

Data-Driven Optimization for Deposition with Degradable Tools

Tony Zheng, Monimoy Bujarbaruah, Francesco Borrelli

We present a data-driven optimization approach for robotic controlled deposition with a degradable tool. Existing methods make the assumption that the tool tip is not changing or i…

eess.SY2023

Increasing Electric Vehicles Utilization in Transit Fleets using Learning, Predictions, Optimization, and Automation

Jacopo Guanetti, Yeojun Kim, Xu Shen +4

This work presents a novel hierarchical approach to increase Battery Electric Buses (BEBs) utilization in transit fleets. The proposed approach relies on three key components. A le…

cs.RO2023★ 12 cited

Energy-Efficient Lane Changes Planning and Control for Connected Autonomous Vehicles on Urban Roads

Eunhyek Joa, Hotae Lee, Eric Yongkeun Choi +1

This paper presents a novel energy-efficient motion planning algorithm for Connected Autonomous Vehicles (CAVs) on urban roads. The approach consists of two components: a decision-…

eess.SY2023

Learning for Online Mixed-Integer Model Predictive Control with Parametric Optimality Certificates

Luigi Russo, Siddharth H. Nair, Luigi Glielmo +1

We propose a supervised learning framework for computing solutions of multi-parametric Mixed Integer Linear Programs (MILPs) that arise in Model Predictive Control. Our approach al…

eess.SY2023

Robust Output-Lifted Learning Model Predictive Control

Siddharth H. Nair, Francesco Borrelli

We propose an iterative approach for designing Robust Learning Model Predictive Control (LMPC) policies for a class of nonlinear systems with additive, unmodelled dynamics. The nom…