1 citations · 1 across the 6 of their papers we have counts for
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Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing
Tommaso Benciolini, Chen Tang, Marion Leibold +3
Autonomous racing creates challenging control problems, but Model Predictive Control (MPC) has made promising steps toward solving both the minimum lap-time problem and head-to-hea…
Double-Iterative Gaussian Process Regression for Modeling Error Compensation in Autonomous Racing
Shaoshu Su, Ce Hao, Catherine Weaver +3
Autonomous racing control is a challenging research problem as vehicles are pushed to their limits of handling to achieve an optimal lap time; therefore, vehicles exhibit highly no…
Skill-Critic: Refining Learned Skills for Hierarchical Reinforcement Learning
Ce Hao, Catherine Weaver, Chen Tang +3
Hierarchical reinforcement learning (RL) can accelerate long-horizon decision-making by temporally abstracting a policy into multiple levels. Promising results in sparse reward env…