Aeronáutica y espacio

Giving AI a Headache: Acoustic Adversarial Attacks to Computer Vision Applications

- Artificial Intelligence (AI) is increasingly used to automate a variety of real-world computer vision (CV) applications, such as autonomous vehicle control, facial recognition, and security cameras....

Safe Reinforcement Learning of Autonomous Highway Driving: A Unified Framework for Safety and Efficiency

- Deep reinforcement learning (DRL) offers a compelling route to decision-making for advanced autonomous vehicles (AVs), yet its trial-and-error nature makes it difficult to guarantee safety during...

Short-Horizon Position Accuracy of Single-Track Models: Implications for Motion Planning of Autonomous Vehicles

- Accurate and computationally efficient vehicle models are essential for motion planning of autonomous vehicles, where positional accuracy directly affects trajectory feasibility and safety. However,...

ReactSim-Bench: Benchmarking Reactive Behavior World Model Simulation in Autonomous Driving

- Reactive capability is a key property of data-driven behavior world model simulators for autonomous driving simulation systems. With this capability, simulated world agents can respond feasibly to...

From Attacks to Curricula: Learnability-Guided Adversarial Training for Safe Autonomous Driving

- Closed-loop adversarial training improves autonomous driving safety by exposing policies to rare safety-critical scenarios. Standard pipelines first generate adversarial scenarios and then sample...

RT-VLA: Real-Time Vision-Language-Action Models via Knowledge Distillation

- Vision-Language-Action (VLA) models have shown strong potential for end-to-end autonomous driving by jointly modeling visual perception, language reasoning, explainability and action prediction....

TetraRL: A Self-Adaptive Runtime for On-Device Deep Reinforcement Learning Systems

- Autonomous robotic systems, including autonomous vehicles, drones, and mobile robots, increasingly rely on on-device Deep Reinforcement Learning (DRL) to adapt to dynamic environments. Unlike...

Multi-Agent Embodied Autonomous Driving: From V2X Information Exchange to Shared World Models

- Autonomous driving is shifting from isolated vehicle intelligence toward multi-agent embodied systems that share perception, infer intent, and coordinate action under uncertainty. This survey...

QueryOcc: Query-based Self-Supervision for 3D Semantic Occupancy

- Learning 3D scene geometry and semantics from images is a core challenge in computer vision and a key capability for autonomous driving. Since large-scale 3D annotation is prohibitively expensive,...

Miniature Testbed for Validating Multi-Agent Cooperative Autonomous Driving

- Cooperative autonomous driving, which extends vehicle autonomy by enabling real-time collaboration between vehicles and smart roadside infrastructure, remains a challenging yet essential problem....

VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models

- Semantic 3D occupancy provides a voxelized world state for autonomous driving and robot decision making, but object and rare-class errors can affect free-space interpretation, collision checking, and...

ERTS: Adversarial Robustness Testing of Ethical AI via Semantic Perturbation in a Bounded Consequence Space

- As AI systems are deployed in high-stakes ethical contexts such as healthcare triage, autonomous vehicle control, and employment screening, formal methods for evaluating their robustness against...

Diffusion Transformer World-Action Model for AV Scene Prediction

- Action-conditioned world models let an autonomous vehicle predict future camera scenes from its own planned controls, enabling planning and simulation without real-world rollouts, but at compact,...

DIMOS: Disentangling Instance-level Moving Object Segmentation

- Moving instance segmentation (MIS) attracts increasing attention due to its broad applications in traffic surveillance, autonomous driving, and animal tracking. Event cameras record asynchronous...

Agentic MPC for Semantic Control System Resynthesis

- While MPC effectively handles structured, diverse, and low-level specifications, it lacks the capability to dynamically incorporate high-level contextual information such as social norms, user...

A Tutorial on World Models and Physical AI

- World modeling is emerging as a central principle for building intelligent systems capable of prediction, reasoning, and decision making. A central distinction can be drawn between explicit world...

VLADriveBench: Evaluating CoT-Action Relationship in VLA for Autonomous Driving

- Vision-language-action (VLA) models generate chain-of-thought (CoT) reasoning alongside driving trajectories, but existing benchmarks evaluate only trajectory quality and do not assess whether the...

Context-Aware Feature-Fusion for Co-occurring Object Detection in Autonomous Driving

- Object detection in autonomous driving requires precise localization and an inherent understanding of the relational context between co-occurring objects. In extremely complex heterogeneous...

DARRMS -- An Efficient Algorithm for Dynamic Attention Radius in Resource-Constrained Multi-Agent Systems

- Multi-agent systems are integral tools for various domains such as robotics, cybersecurity, and autonomous vehicle planning. These types of systems often have constraints on the computational...

From Imitation to Alignment: Human-Preference Flow Policies for Long-Horizon Sidewalk Navigation

- Autonomous long-horizon sidewalk navigation is essential for micro-mobility applications such as robotic food delivery and assistive electronic wheelchairs. Unlike autonomous driving on the road,...

VLGA: Vision-Language-Geometry-Action Models for Autonomous Driving

- Vision-language-action (VLA) models can describe scenes and reason about them in language, yet still struggle to ground their actions in the dense 3D world around them. Existing approaches either...