Search Results for author: Paolo Falcone

Found 7 papers, 0 papers with code

Collective Decision Making using Attractive and Repulsive Forces in Markovian Opinion Dynamics

no code implementations21 Mar 2022 Carl-Johan Heiker, Paolo Falcone

In this paper, we model a decision making process in a network of interacting agents using Markovian opinion dynamics, where each agent switches between decisions according to a continuous time Markov chain.

Autonomous Vehicles Decision Making

A Semi-Distributed Interior Point Algorithm for Optimal Coordination of Automated Vehicles at Intersections

no code implementations19 Nov 2021 Robert Hult, Mario Zanon, Sebastien Gros, Paolo Falcone

In this paper, we consider the optimal coordination of automated vehicles at intersections under fixed crossing orders.

Distributed Optimization

Model Predictive Control with Infeasible Reference Trajectories

no code implementations10 Sep 2021 Ivo Batkovic, Mohammad Ali, Paolo Falcone, Mario Zanon

Model Predictive Control (MPC) formulations are typically built on the requirement that a feasible reference trajectory is available.

Computation of Parameter Dependent Robust Invariant Sets for LPV Models with Guaranteed Performance

no code implementations21 Sep 2020 Ankit Gupta, Manas Mejari, Paolo Falcone, Dario Piga

This paper presents an iterative algorithm to compute a Robust Control Invariant (RCI) set, along with an invariance-inducing control law, for Linear Parameter-Varying (LPV) systems.

ParkPredict: Motion and Intent Prediction of Vehicles in Parking Lots

no code implementations21 Apr 2020 Xu Shen, Ivo Batkovic, Vijay Govindarajan, Paolo Falcone, Trevor Darrell, Francesco Borrelli

We investigate the problem of predicting driver behavior in parking lots, an environment which is less structured than typical road networks and features complex, interactive maneuvers in a compact space.

Safe Trajectory Tracking in Uncertain Environments

no code implementations30 Jan 2020 Ivo Batkovic, Mohammad Ali, Paolo Falcone, Mario Zanon

In Model Predictive Control (MPC) formulations of trajectory tracking problems, infeasible reference trajectories and a-priori unknown constraints can lead to cumbersome designs, aggressive tracking, and loss of recursive feasibility.

A Computationally Efficient Model for Pedestrian Motion Prediction

no code implementations13 Mar 2018 Ivo Batkovic, Mario Zanon, Nils Lubbe, Paolo Falcone

We present a mathematical model to predict pedestrian motion over a finite horizon, intended for use in collision avoidance algorithms for autonomous driving.

Systems and Control

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