227 citations · 246 across the 5 of their papers we have counts for
4 papers · 1 filter
Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight
Katie Kang, Suneel Belkhale, Gregory Kahn +2
Deep reinforcement learning provides a promising approach for vision-based control of real-world robots. However, the generalization of such models depends critically on the quanti…
Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty
Rowan McAllister, Gregory Kahn, Jeff Clune +1
Deep learning provides a powerful tool for machine perception when the observations resemble the training data. However, real-world robotic systems must react intelligently to thei…
Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning
Anusha Nagabandi, Gregory Kahn, Ronald S. Fearing +1
Model-free deep reinforcement learning algorithms have been shown to be capable of learning a wide range of robotic skills, but typically require a very large number of samples to…
Uncertainty-Aware Reinforcement Learning for Collision Avoidance
Gregory Kahn, Adam Villaflor, Vitchyr Pong +2
Reinforcement learning can enable complex, adaptive behavior to be learned automatically for autonomous robotic platforms. However, practical deployment of reinforcement learning m…