activity
20172026
most citedMultimodal End-to-End Autonomous Driving

316 citations · 611 across the 7 of their papers we have counts for

collaborators

9 papers

cs.RO2026

FORMICA: Decision-Focused Learning for Communication-Free Multi-Robot Task Allocation

Antonio Lopez, Jack Muirhead, Carlo Pinciroli

Most multi-robot task allocation methods rely on communication to resolve conflicts and reach consistent assignments. In environments with limited bandwidth, degraded infrastructur…

cs.CV2026

Addressing the Waypoint-Action Gap in End-to-End Autonomous Driving via Vehicle Motion Models

Jorge Daniel Rodríguez-Vidal, Gabriel Villalonga, Diego Porres +1

End-to-End Autonomous Driving (E2E-AD) systems are typically grouped by the nature of their outputs: (i) waypoint-based models that predict a future trajectory, and (ii) action-bas…

eess.SY2024★ 1 cited

Decomposing Control Lyapunov Functions for Efficient Reinforcement Learning

Antonio Lopez, David Fridovich-Keil

Recent methods using Reinforcement Learning (RL) have proven to be successful for training intelligent agents in unknown environments. However, RL has not been applied widely in re…

cs.CV2023

Scaling Vision-based End-to-End Driving with Multi-View Attention Learning

Yi Xiao, Felipe Codevilla, Diego Porres +1

On end-to-end driving, human driving demonstrations are used to train perception-based driving models by imitation learning. This process is supervised on vehicle signals (e.g., st…

cs.CV2020★ 5 cited

Action-Based Representation Learning for Autonomous Driving

Yi Xiao, Felipe Codevilla, Christopher Pal +1

Human drivers produce a vast amount of data which could, in principle, be used to improve autonomous driving systems. Unfortunately, seemingly straightforward approaches for creati…

cs.CV2019★ 316 cited

Multimodal End-to-End Autonomous Driving

Yi Xiao, Felipe Codevilla, Akhil Gurram +2

A crucial component of an autonomous vehicle (AV) is the artificial intelligence (AI) is able to drive towards a desired destination. Today, there are different paradigms addressin…