1 citations · 2 across the 4 of their papers we have counts for
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TADPO: Reinforcement Learning Goes Off-road
Zhouchonghao Wu, Raymond Song, Vedant Mundheda +3
Off-road autonomous driving poses significant challenges such as navigating unmapped, variable terrain with uncertain and diverse dynamics. Addressing these challenges requires eff…
Planning with Adaptive World Models for Autonomous Driving
Arun Balajee Vasudevan, Neehar Peri, Jeff Schneider +1
Motion planning is crucial for safe navigation in complex urban environments. Historically, motion planners (MPs) have been evaluated with procedurally-generated simulators like CA…
Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving
Adam Villaflor, Brian Yang, Huangyuan Su +3
Significant progress has been made in training multimodal trajectory forecasting models for autonomous driving. However, effectively integrating these models with downstream planne…