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cs.RO2025
ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving
Renju Feng, Ning Xi, Duanfeng Chu +6
This paper presents ARTEMIS, an end-to-end autonomous driving framework that combines autoregressive trajectory planning with Mixture-of-Experts (MoE). Traditional modular methods…
cs.RO2024
EPN: An Ego Vehicle Planning-Informed Network for Target Trajectory Prediction
Saiqian Peng, Duanfeng Chu, Guanjie Li +2
Trajectory prediction plays a crucial role in improving the safety of autonomous vehicles. However, due to the highly dynamic and multimodal nature of the task, accurately predicti…