:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Baumann, Nicolas, Hu, Cheng, Sivasothilingam, Paviththiren, Qin, Haotong, Xie, Lei, Magno, Michele, Benini, Luca
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Artificial Intelligence Robotics
Accesso online:	https://arxiv.org/abs/2504.11514
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

RobotxR1: Enabling Embodied Robotic Intelligence on Large Language Models through Closed-Loop Reinforcement Learning
di: Boyle, Liam, et al.
Pubblicazione: (2025)

Drive Fast, Learn Faster: On-Board RL for High Performance Autonomous Racing
di: Hildisch, Benedict, et al.
Pubblicazione: (2025)

FSDP: Fast and Safe Data-Driven Overtaking Trajectory Planning for Head-to-Head Autonomous Racing Competitions
di: Hu, Cheng, et al.
Pubblicazione: (2025)

GP-enhanced Autonomous Drifting Framework using ADMM-based iLQR
di: Xie, Yangyang, et al.
Pubblicazione: (2025)

Learning-Based On-Track System Identification for Scaled Autonomous Racing in Under a Minute
di: Dikici, Onur, et al.
Pubblicazione: (2024)

RLPP: A Residual Method for Zero-Shot Real-World Autonomous Racing on Scaled Platforms
di: Ghignone, Edoardo, et al.
Pubblicazione: (2025)

TinyCenterSpeed: Efficient Center-Based Object Detection for Autonomous Racing
di: Reichlin, Neil, et al.
Pubblicazione: (2025)

R-CARLA: High-Fidelity Sensor Simulations with Interchangeable Dynamics for Autonomous Racing
di: Brunner, Maurice, et al.
Pubblicazione: (2025)

Robust and Efficient Depth-based Obstacle Avoidance for Autonomous Miniaturized UAVs
di: Müller, Hanna, et al.
Pubblicazione: (2022)

Robustness Evaluation of Localization Techniques for Autonomous Racing
di: Lim, Tian Yi, et al.
Pubblicazione: (2024)

STCLocker: Deadlock Avoidance Testing for Autonomous Driving Systems
di: Cheng, Mingfei, et al.
Pubblicazione: (2025)

Predictive Spliner: Data-Driven Overtaking in Autonomous Racing Using Opponent Trajectory Prediction
di: Baumann, Nicolas, et al.
Pubblicazione: (2024)

DTR: Delaunay Triangulation-based Racing for Scaled Autonomous Racing
di: Tognoni, Luca, et al.
Pubblicazione: (2025)

M-Predictive Spliner: Enabling Spatiotemporal Multi-Opponent Overtaking for Autonomous Racing
di: Imholz, Nadine, et al.
Pubblicazione: (2025)

Ultra-Lightweight Collaborative Mapping for Robot Swarms
di: Niculescu, Vlad, et al.
Pubblicazione: (2024)

NanoSLAM: Enabling Fully Onboard SLAM for Tiny Robots
di: Niculescu, Vlad, et al.
Pubblicazione: (2023)

Fully Onboard Low-Power Localization with Semantic Sensor Fusion on a Nano-UAV using Floor Plans
di: Zimmerman, Nicky, et al.
Pubblicazione: (2023)

BatDeck -- Ultra Low-power Ultrasonic Ego-velocity Estimation and Obstacle Avoidance on Nano-drones
di: Müller, Hanna, et al.
Pubblicazione: (2024)

BatDeck: Advancing Nano-drone Navigation with Low-power Ultrasound-based Obstacle Avoidance
di: Müller, Hanna, et al.
Pubblicazione: (2024)

Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO
di: Moosmann, Julian, et al.
Pubblicazione: (2023)

Robust Spatiotemporal Motion Planning for Multi-Agent Autonomous Racing via Topological Gap Identification and Accelerated MPC
di: Zhang, Mingyi, et al.
Pubblicazione: (2026)

Fully Onboard SLAM for Distributed Mapping with a Swarm of Nano-Drones
di: Friess, Carl, et al.
Pubblicazione: (2023)

Large Language Models for Human-like Autonomous Driving: A Survey
di: Li, Yun, et al.
Pubblicazione: (2024)

DriveVLM-RL: Neuroscience-Inspired Reinforcement Learning with Vision-Language Models for Safe and Deployable Autonomous Driving
di: Huang, Zilin, et al.
Pubblicazione: (2026)

LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model
di: Li, Xiangyu, et al.
Pubblicazione: (2026)

Efficient and Accurate Downfacing Visual Inertial Odometry
di: Kühne, Jonas, et al.
Pubblicazione: (2025)

LEVIO: Lightweight Embedded Visual Inertial Odometry for Resource-Constrained Devices
di: Kühne, Jonas, et al.
Pubblicazione: (2026)

AppleVLM: End-to-end Autonomous Driving with Advanced Perception and Planning-Enhanced Vision-Language Models
di: Han, Yuxuan, et al.
Pubblicazione: (2026)

Edge-Cloud Collaborative Motion Planning for Autonomous Driving with Large Language Models
di: Chen, Jiao, et al.
Pubblicazione: (2024)

Event-Priori-Based Vision-Language Model for Efficient Visual Understanding
di: Qin, Haotong, et al.
Pubblicazione: (2025)

Learning to Model Diverse Driving Behaviors in Highly Interactive Autonomous Driving Scenarios with Multi-Agent Reinforcement Learning
di: Weiwei, Liu, et al.
Pubblicazione: (2024)

ExpertAD: Enhancing Autonomous Driving Systems with Mixture of Experts
di: Jiang, Haowen, et al.
Pubblicazione: (2025)

On-Board Vision-Language Models for Personalized Autonomous Vehicle Motion Control: System Design and Real-World Validation
di: Cui, Can, et al.
Pubblicazione: (2024)

Leveraging Large Language Models for Enhancing Autonomous Vehicle Perception
di: Karagounis, Athanasios
Pubblicazione: (2024)

Diffusion Models for Safety Validation of Autonomous Driving Systems
di: Wang, Juanran, et al.
Pubblicazione: (2025)

Human-like Semantic Navigation for Autonomous Driving using Knowledge Representation and Large Language Models
di: Ballardini, Augusto Luis, et al.
Pubblicazione: (2025)

Nav-EE: Navigation-Guided Early Exiting for Efficient Vision-Language Models in Autonomous Driving
di: Hu, Haibo, et al.
Pubblicazione: (2025)

LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving
di: Zhang, Yuhang, et al.
Pubblicazione: (2025)

Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models
di: Mei, Yuewen, et al.
Pubblicazione: (2025)

PKRD-CoT: A Unified Chain-of-thought Prompting for Multi-Modal Large Language Models in Autonomous Driving
di: Luo, Xuewen, et al.
Pubblicazione: (2024)