1 citations · 2 across the 4 of their papers we have counts for
4 papers
UniMM: A Unified Mixture Model Framework for Multi-Agent Simulation
Longzhong Lin, Xuewu Lin, Kechun Xu +4
Simulation plays a crucial role in assessing autonomous driving systems, where the generation of realistic multi-agent behaviors is a key aspect. In multi-agent simulation, the pri…
HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Driving
Hongyu Zhou, Longzhong Lin, Jiabao Wang +6
In the past few decades, autonomous driving algorithms have made significant progress in perception, planning, and control. However, evaluating individual components does not fully…
EDA: Evolving and Distinct Anchors for Multimodal Motion Prediction
Longzhong Lin, Xuewu Lin, Tianwei Lin +3
Motion prediction is a crucial task in autonomous driving, and one of its major challenges lands in the multimodality of future behaviors. Many successful works have utilized mixtu…
Learning Observation-Based Certifiable Safe Policy for Decentralized Multi-Robot Navigation
Yuxiang Cui, Longzhong Lin, Xiaolong Huang +3
Safety is of great importance in multi-robot navigation problems. In this paper, we propose a control barrier function (CBF) based optimizer that ensures robot safety with both hig…