Showing cs.ROShow all
3 papers · 1 filter
cs.RO2026
Efficient Real-World Autonomous Racing via Attenuated Residual Policy Optimization
Raphael Trumpp, Denis Hoornaert, Mirco Theile +1
Residual policy learning (RPL), in which a learned policy refines a static base policy using deep reinforcement learning (DRL), has shown strong performance across various robotic…
cs.RO2024
RaceMOP: Mapless Online Path Planning for Multi-Agent Autonomous Racing using Residual Policy Learning
Raphael Trumpp, Ehsan Javanmardi, Jin Nakazato +2
The interactive decision-making in multi-agent autonomous racing offers insights valuable beyond the domain of self-driving cars. Mapless online path planning is particularly of pr…
cs.RO2024
Unifying F1TENTH Autonomous Racing: Survey, Methods and Benchmarks
Benjamin David Evans, Raphael Trumpp, Marco Caccamo +4
The F1TENTH autonomous driving platform, consisting of 1:10-scale remote-controlled cars, has evolved into a well-established education and research platform. The many publications…