15 citations · 42 across the 7 of their papers we have counts for
8 papers
X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback
Jensen Gao, Siddharth Reddy, Glen Berseth +5
We aim to help users communicate their intent to machines using flexible, adaptive interfaces that translate arbitrary user input into desired actions. In this work, we focus on as…
ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning
Sean Chen, Jensen Gao, Siddharth Reddy +3
Building assistive interfaces for controlling robots through arbitrary, high-dimensional, noisy inputs (e.g., webcam images of eye gaze) can be challenging, especially when it invo…
DisCo RL: Distribution-Conditioned Reinforcement Learning for General-Purpose Policies
Soroush Nasiriany, Vitchyr H. Pong, Ashvin Nair +3
Can we use reinforcement learning to learn general-purpose policies that can perform a wide range of different tasks, resulting in flexible and reusable skills? Contextual policies…
Reinforcement Learning for Robust Parameterized Locomotion Control of Bipedal Robots
Zhongyu Li, Xuxin Cheng, Xue Bin Peng +4
Developing robust walking controllers for bipedal robots is a challenging endeavor. Traditional model-based locomotion controllers require simplifying assumptions and careful model…
Ecological Reinforcement Learning
John D. Co-Reyes, Suvansh Sanjeev, Glen Berseth +2
Much of the current work on reinforcement learning studies episodic settings, where the agent is reset between trials to an initial state distribution, often with well-shaped rewar…
Morphology-Agnostic Visual Robotic Control
Brian Yang, Dinesh Jayaraman, Glen Berseth +2
Existing approaches for visuomotor robotic control typically require characterizing the robot in advance by calibrating the camera or performing system identification. We propose M…