Search Results for author: Emilio Frazzoli

Found 34 papers, 8 papers with code

Reliability-aware Control of Power Converters in Mobility Applications

no code implementations29 Nov 2023 Amin Rezaeizadeh, Gioele Zardini, Emilio Frazzoli, Silvia Mastellone

This paper introduces an automatic control method designed to enhance the operation of electric vehicles, besides the speed tracking objectives, by including reliability and lifetime requirements.

A Counterfactual Safety Margin Perspective on the Scoring of Autonomous Vehicles' Riskiness

1 code implementation2 Aug 2023 Alessandro Zanardi, Andrea Censi, Margherita Atzei, Luigi Di Lillo, Emilio Frazzoli

Autonomous Vehicles (AVs) promise a range of societal advantages, including broader access to mobility, reduced road accidents, and enhanced transportation efficiency.

Autonomous Vehicles counterfactual

Factorization of Multi-Agent Sampling-Based Motion Planning

1 code implementation1 Apr 2023 Alessandro Zanardi, Pietro Zullo, Andrea Censi, Emilio Frazzoli

Although standard Sampling-based Algorithms (SBAs) can be used to search for solutions in the robots' joint space, this approach quickly becomes computationally intractable as the number of agents increases.

Motion Planning

CARMA: Fair and efficient bottleneck congestion management via non-tradable karma credits

no code implementations15 Aug 2022 Ezzat Elokda, Carlo Cenedese, Kenan Zhang, Andrea Censi, John Lygeros, Emilio Frazzoli, Florian Dörfler

In our CARMA scheme, the bottleneck is divided into a fast lane that is kept in free flow and a slow lane that is subject to congestion.

Fairness Management +1

Compositional Controller Synthesis for Interconnected Stochastic Systems with Markovian Switching

no code implementations6 Aug 2022 Abolfazl Lavaei, Emilio Frazzoli

We apply our results to a room temperature network of 200 rooms with Markovian switching signals while accepting multiple storage certificates.

Safety Barrier Certificates for Stochastic Hybrid Systems

no code implementations6 Aug 2022 Abolfazl Lavaei, Sadegh Soudjani, Emilio Frazzoli

In our proposed scheme, we first provide an augmented framework to characterize each stochastic hybrid system containing continuous evolutions and instantaneous jumps with a unified system covering both scenarios.

A self-contained karma economy for the dynamic allocation of common resources

no code implementations1 Jul 2022 Ezzat Elokda, Saverio Bolognani, Andrea Censi, Florian Dörfler, Emilio Frazzoli

This paper presents karma mechanisms, a novel approach to the repeated allocation of a scarce resource among competing agents over an infinite time.

Fairness

Constructing MDP Abstractions Using Data with Formal Guarantees

no code implementations29 Jun 2022 Abolfazl Lavaei, Sadegh Soudjani, Emilio Frazzoli, Majid Zamani

We then propose a scenario convex program (SCP) associated to the original RCP by collecting a finite number of data from trajectories of the system.

Data-Driven Synthesis of Symbolic Abstractions with Guaranteed Confidence

no code implementations19 Jun 2022 Abolfazl Lavaei, Emilio Frazzoli

In this work, we propose a data-driven approach for the construction of finite abstractions (a. k. a., symbolic models) for discrete-time deterministic control systems with unknown dynamics.

Task-driven Modular Co-design of Vehicle Control Systems

1 code implementation30 Mar 2022 Gioele Zardini, Zelio Suter, Andrea Censi, Emilio Frazzoli

When designing autonomous systems, we need to consider multiple trade-offs at various abstraction levels, and the choices of single (hardware and software) components need to be studied jointly.

Formal Estimation of Collision Risks for Autonomous Vehicles: A Compositional Data-Driven Approach

no code implementations14 Dec 2021 Abolfazl Lavaei, Luigi Di Lillo, Andrea Censi, Emilio Frazzoli

The proposed approach is based on the construction of sub-barrier certificates for each stochastic agent via a set of data collected from its trajectories while providing an a-priori guaranteed confidence on the data-driven estimation.

Autonomous Vehicles

Analysis and Control of Autonomous Mobility-on-Demand Systems

no code implementations28 Jun 2021 Gioele Zardini, Nicolas Lanzetti, Marco Pavone, Emilio Frazzoli

We provide a comprehensive review of methods and tools to model and solve problems related to autonomous mobility-on-demand systems.

Autonomous Vehicles

Rule-based Optimal Control for Autonomous Driving

no code implementations14 Jan 2021 Wei Xiao, Noushin Mehdipour, Anne Collin, Amitai Bin-Nun, Emilio Frazzoli, Radboud Duintjer Tebbens, Calin Belta

We develop optimal control strategies for Autonomous Vehicles (AVs) that are required to meet complex specifications imposed by traffic laws and cultural expectations of reasonable driving behavior.

Autonomous Driving Robotics Systems and Control Systems and Control

The Negative Pretraining Effect in Sequential Deep Learning and Three Ways to Fix It

no code implementations1 Jan 2021 Julian G. Zilly, Franziska Eckert, Bhairav Mehta, Andrea Censi, Emilio Frazzoli

Negative pretraining is a prominent sequential learning effect of neural networks where a pretrained model obtains a worse generalization performance than a model that is trained from scratch when either are trained on a target task.

Co-Design of Autonomous Systems: From Hardware Selection to Control Synthesis

no code implementations21 Nov 2020 Gioele Zardini, Andrea Censi, Emilio Frazzoli

In this work, we consider the problem of co-designing the control algorithm as well as the platform around it.

A Compositional Sheaf-Theoretic Framework for Event-Based Systems (Extended Version)

no code implementations10 May 2020 Gioele Zardini, David I. Spivak, Andrea Censi, Emilio Frazzoli

A compositional sheaf-theoretic framework for the modeling of complex event-based systems is presented.

Quantifying the effect of representations on task complexity

no code implementations19 Dec 2019 Julian Zilly, Lorenz Hetzel, Andrea Censi, Emilio Frazzoli

To quantify this alignment effect of data representations on the difficulty of a learning task, we make use of an existing task complexity score and show its connection to the representation-dependent information coding length of the input.

The Frechet Distance of training and test distribution predicts the generalization gap

no code implementations25 Sep 2019 Julian Zilly, Hannes Zilly, Oliver Richter, Roger Wattenhofer, Andrea Censi, Emilio Frazzoli

Empirically across several data domains, we substantiate this viewpoint by showing that test performance correlates strongly with the distance in data distributions between training and test set.

Learning Theory Transfer Learning

Today Me, Tomorrow Thee: Efficient Resource Allocation in Competitive Settings using Karma Games

no code implementations22 Jul 2019 Andrea Censi, Saverio Bolognani, Julian G. Zilly, Shima Sadat Mousavi, Emilio Frazzoli

We present a new type of coordination mechanism among multiple agents for the allocation of a finite resource, such as the allocation of time slots for passing an intersection.

Landmark Guided Probabilistic Roadmap Queries

1 code implementation6 Apr 2017 Brian Paden, Yannik Nager, Emilio Frazzoli

A landmark based heuristic is investigated for reducing query phase run-time of the probabilistic roadmap (\PRM) motion planning method.

Motion Planning

Set-Point Regulation of Linear Continuous-Time Systems using Neuromorphic Vision Sensors

no code implementations18 Sep 2016 Prince Singh, Sze Zheng Yong, Emilio Frazzoli

Recently developed neuromorphic vision sensors have become promising candidates for agile and autonomous robotic applications primarily due to, in particular, their high temporal resolution and low latency.

A Generalized Label Correcting Method for Optimal Kinodynamic Motion Planning

3 code implementations23 Jul 2016 Brian Paden, Emilio Frazzoli

A resolution complete optimal kinodynamic motion planning algorithm is presented and described as a generalized label correcting (GLC) method.

Robotics

A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles

4 code implementations25 Apr 2016 Brian Paden, Michal Cap, Sze Zheng Yong, Dmitry Yershov, Emilio Frazzoli

Self-driving vehicles are a maturing technology with the potential to reshape mobility by enhancing the safety, accessibility, efficiency, and convenience of automotive transportation.

Robotics

POMDP-lite for Robust Robot Planning under Uncertainty

no code implementations16 Feb 2016 Min Chen, Emilio Frazzoli, David Hsu, Wee Sun Lee

We show that a POMDP-lite is equivalent to a set of fully observable Markov decision processes indexed by a hidden parameter and is useful for modeling a variety of interesting robotic tasks.

Reinforcement Learning (RL)

Free-configuration Biased Sampling for Motion Planning: Errata

no code implementations3 Nov 2013 Joshua Bialkowski, Michael Otte, Emilio Frazzoli

This document contains improved and updated proofs of convergence for the sampling method presented in our paper "Free-configuration Biased Sampling for Motion Planning".

Motion Planning

Fast Collision Checking: From Single Robots to Multi-Robot Teams

no code implementations10 May 2013 Joshua Bialkowski, Michael Otte, Emilio Frazzoli

We examine three different algorithms that enable the collision certificate method from [Bialkowski, et al.] to handle the case of a centralized multi-robot team.

Sampling-based Algorithms for Optimal Motion Planning

4 code implementations5 May 2011 Sertac Karaman, Emilio Frazzoli

The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically optimal, i. e., such that the cost of the returned solution converges almost surely to the optimum.

Robotics

Incremental Sampling-based Algorithms for Optimal Motion Planning

3 code implementations3 May 2010 Sertac Karaman, Emilio Frazzoli

Second, a new algorithm is considered, called the Rapidly-exploring Random Graph (RRG), and it is shown that the cost of the best path in the RRG converges to the optimum almost surely.

Robotics 68T40

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