1 citations · 2 across the 4 of their papers we have counts for
4 papers
A Learning-based Planning and Control Framework for Inertia Drift Vehicles
Bei Zhou, Zhouheng Li, Lei Xie +2
Inertia drift is a transitional maneuver between two sustained drift stages in opposite directions, which provides valuable insights for navigating consecutive sharp corners for au…
Safe Reinforcement Learning with a Predictive Safety Filter for Motion Planning and Control: A Drifting Vehicle Example
Bei Zhou, Baha Zarrouki, Mattia Piccinini +3
Autonomous drifting is a complex and crucial maneuver for safety-critical scenarios like slippery roads and emergency collision avoidance, requiring precise motion planning and con…
Adaptive Learning-based Model Predictive Control Strategy for Drift Vehicles
Bei Zhou, Cheng Hu, Jun Zeng +4
Drift vehicle control offers valuable insights to support safe autonomous driving in extreme conditions, which hinges on tracking a particular path while maintaining the vehicle st…
A Data-Driven Aggressive Autonomous Racing Framework Utilizing Local Trajectory Planning with Velocity Prediction
Zhouheng Li, Bei Zhou, Cheng Hu +2
The development of autonomous driving has boosted the research on autonomous racing. However, existing local trajectory planning methods have difficulty planning trajectories with…