Cover Image

Accelerating Real-World Overtaking in F1TENTH Racing Employing Reinforcement Learning Methods

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Steiner, Emily, van der Spuy, Daniel, Zhou, Futian, Pama, Afereti, Liarokapis, Minas, Williams, Henry
Format:	Preprint
Published:	2025
Subjects:	Robotics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unifying F1TENTH Autonomous Racing: Survey, Methods and Benchmarks
by: Evans, Benjamin David, et al.
Published: (2024)

Hardware Neural Control of CartPole and F1TENTH Race Car
by: Paluch, Marcin, et al.
Published: (2024)

Advancing Autonomous Racing: A Comprehensive Survey of the RoboRacer (F1TENTH) Platform
by: Charles, Israel, et al.
Published: (2025)

Trajectory Planning Using Reinforcement Learning for Interactive Overtaking Maneuvers in Autonomous Racing Scenarios
by: Ögretmen, Levent, et al.
Published: (2024)

Benchmarking Reinforcement Learning Methods for Dexterous Robotic Manipulation with a Three-Fingered Gripper
by: Cutler, Elizabeth, et al.
Published: (2024)

A cable‐driven underwater robotic system for delicate manipulation of marine biology samples
by: Mahmoud Zarebidoki, et al.
Published: (2024)

ARGOS: An Automaton Referencing Guided Overtake System for Head-to-Head Autonomous Racing
by: Sukhil, Varundev, et al.
Published: (2024)

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

DBF-MA: A Differential Bayesian Filtering Planner for Multi-Agent Autonomous Racing Overtakes
by: Weiss, Trent, et al.
Published: (2025)

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

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

End2Race: Efficient End-to-End Imitation Learning for Real-Time F1Tenth Racing
by: Qiao, Zhijie, et al.
Published: (2025)

F1tenth Autonomous Racing With Offline Reinforcement Learning Methods
by: Koirala, Prajwal, et al.
Published: (2024)

TinyLidarNet: 2D LiDAR-based End-to-End Deep Learning Model for F1TENTH Autonomous Racing
by: Zarrar, Mohammed Misbah, et al.
Published: (2024)

Learning Based High-Level Decision Making for Abortable Overtaking in Autonomous Vehicles
by: Malayjerdi, Ehsan, et al.
Published: (2022)

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

Efficient Real-World Autonomous Racing via Attenuated Residual Policy Optimization
by: Trumpp, Raphael, et al.
Published: (2026)

Zero-Shot Sim-to-Real Reinforcement Learning for Fruit Harvesting
by: Williams, Emlyn, et al.
Published: (2025)

An Overtaking Trajectory Planning Framework Based on Spatio-temporal Topology and Reachable Set Analysis Ensuring Time Efficiency
by: Mao, Wule, et al.
Published: (2024)

Reinforced Embodied Planning with Verifiable Reward for Real-World Robotic Manipulation
by: Bo, Zitong, et al.
Published: (2025)

Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks
by: Valencia, David, et al.
Published: (2024)

Dexterous Grasping with Real-World Robotic Reinforcement Learning
by: Huang, Dongchi, et al.
Published: (2025)

Scenario Extraction from a Large Real-World Dataset for the Assessment of Automated Vehicles
by: Guo, Detian, et al.
Published: (2023)

Curriculum Reinforcement Learning for Quadrotor Racing with Random Obstacles
by: Sun, Fangyu, et al.
Published: (2026)

TwinRL: Digital Twin-Driven Reinforcement Learning for Real-World Robotic Manipulation
by: Xu, Qinwen, et al.
Published: (2026)

Autonomous Vehicle Collision Avoidance With Racing Parameterized Deep Reinforcement Learning
by: Sivashangaran, Shathushan, et al.
Published: (2026)

From Zero to High-Speed Racing: An Autonomous Racing Stack
by: Jardali, Hassan, et al.
Published: (2025)

A Simulation Pipeline to Facilitate Real-World Robotic Reinforcement Learning Applications
by: Silveira, Jefferson, et al.
Published: (2025)

Reset-Free Reinforcement Learning for Real-World Agile Driving: An Empirical Study
by: Honda, Kohei, et al.
Published: (2026)

Safety Reinforced Model Predictive Control (SRMPC): Improving MPC with Reinforcement Learning for Motion Planning in Autonomous Driving
by: Fischer, Johannes, et al.
Published: (2025)

Genie Centurion: Accelerating Scalable Real-World Robot Training with Human Rewind-and-Refine Guidance
by: Wang, Wenhao, et al.
Published: (2025)

Accelerating Autonomy: Insights from Pro Racers in the Era of Autonomous Racing - An Expert Interview Study
by: Werner, Frederik, et al.
Published: (2024)

A Vision-Language-Action-Critic Model for Robotic Real-World Reinforcement Learning
by: Zhai, Shaopeng, et al.
Published: (2025)

LiRA: Light-Robust Adversary for Model-based Reinforcement Learning in Real World
by: Kobayashi, Taisuke
Published: (2024)

RUMOR: Reinforcement learning for Understanding a Model of the Real World for Navigation in Dynamic Environments
by: Martinez-Baselga, Diego, et al.
Published: (2024)

Tac2Real: Reliable and GPU Visuotactile Simulation for Online Reinforcement Learning and Zero-Shot Real-World Deployment
by: Yan, Ningyu, et al.
Published: (2026)

Learning Tactile Insertion in the Real World
by: Palenicek, Daniel, et al.
Published: (2024)

Learning Autonomous Race Driving with Action Mapping Reinforcement Learning
by: Wang, Yuanda, et al.
Published: (2024)

Context-Aware Model-Based Reinforcement Learning for Autonomous Racing
by: Moustafa, Emran Yasser, et al.
Published: (2025)

IteraOptiRacing: A Unified Planning-Control Framework for Real-time Autonomous Racing for Iterative Optimal Performance
by: Zeng, Yifan, et al.
Published: (2025)