4 papers
Meta-Policy Learning over Plan Ensembles for Robust Articulated Object Manipulation
Constantinos Chamzas, Caelan Garrett, Balakumar Sundaralingam +2
Recent work has shown that complex manipulation skills, such as pushing or pouring, can be learned through state-of-the-art learning based techniques, such as Reinforcement Learnin…
Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning
Michelle A. Lee, Carlos Florensa, Jonathan Tremblay +4
Traditional robotic approaches rely on an accurate model of the environment, a detailed description of how to perform the task, and a robust perception system to keep track of the…
IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data
Ajay Mandlekar, Fabio Ramos, Byron Boots +4
Learning from offline task demonstrations is a problem of great interest in robotics. For simple short-horizon manipulation tasks with modest variation in task instances, offline l…
Guided Policy Search with Delayed Sensor Measurements
Connor Schenck, Dieter Fox
Guided policy search is a method for reinforcement learning that trains a general policy for accomplishing a given task by guiding the learning of the policy with multiple guiding…