15 citations · 39 across the 15 of their papers we have counts for
5 papers · 1 filter
Slow Brain, Fast Planner: Latency-Resilient VLM-Augmented Urban Navigation
Zhenghao "Mark'' Peng, Honglin He, Quanyi Li +2
Learning-based planners for sidewalk navigation can generate diverse candidate trajectories in real time, yet their scoring functions often fail to select the best trajectory in ch…
SceneStreamer: Continuous Scenario Generation as Next Token Group Prediction
Zhenghao Peng, Yuxin Liu, Bolei Zhou
Realistic and interactive traffic simulation is essential for training and evaluating autonomous driving systems. However, most existing data-driven simulation methods rely on stat…
Adv-BMT: Bidirectional Motion Transformer for Safety-Critical Traffic Scenario Generation
Yuxin Liu, Zhenghao Peng, Xuanhao Cui +1
Scenario-based testing is essential for validating the performance of autonomous driving (AD) systems. However, such testing is limited by the scarcity of long-tailed, safety-criti…
Data-Efficient Learning from Human Interventions for Mobile Robots
Zhenghao Peng, Zhizheng Liu, Bolei Zhou
Mobile robots are essential in applications such as autonomous delivery and hospitality services. Applying learning-based methods to address mobile robot tasks has gained popularit…
Improving the Generalization of End-to-End Driving through Procedural Generation
Quanyi Li, Zhenghao Peng, Qihang Zhang +2
Over the past few years there is a growing interest in the learning-based self driving system. To ensure safety, such systems are first developed and validated in simulators before…