Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning
December 2022
An exploration of embodied visual exploration
May 2021
Digit: A novel design for a low-cost compact high-resolution tactile sensor with application to in-hand manipulation
We design and demonstrate a new tactile sensor for in-hand tactile manipulation in a robotic hand.
May 2020
Manipulation by feel: Touch-based control with deep predictive models
High-resolution tactile sensing together with visual approaches to prediction and planning with deep neural networks enables high-precision tactile servoing tasks.
May 2019
Emergence of exploratory look-around behaviors through active observation completion
May 2019
More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch
By exploiting high precision tactile sensing with deep learning, robots can effectively iteratively adjust their grasp configurations to boost grasping performance from 65% to 94%.
October 2018
End-to-end policy learning for active visual categorization
Active visual perception with realistic and complex imagery can be formulated as an end-to-end reinforcement learning problem, the solution to which benefits from additionally exploiting the auxiliary task of action-conditioned future prediction.
July 2018
Learning to look around: Intelligently exploring unseen environments for unknown tasks
Task-agnostic visual exploration policies may be trained through a proxy "observation completion" task that requires an agent to "paint" unobserved views given a small set of observed views.
June 2018
Learning Image Representations Tied to Egomotion from Unlabeled Video
An agent's continuous visual observations include information about how the world responds to its actions. This can provide an effective source of self-supervision for learning visual representations.
December 2017
Embodied learning for visual recognition
January 2017
Pano2Vid: Automatic cinematography for watching 360-degree videos
By exploiting human-uploaded web videos as weak supervision, we may train a system that learns what good videos look like, and tries to automatically direct a virtual camera through precaptured 360-degree videos to try to produce human-like videos.
November 2016
Look-ahead before you leap: end-to-end active recognition by forecasting the effect of motion
Active visual perception with realistic and complex imagery can be formulated as an end-to-end reinforcement learning problem, the solution to which benefits from additionally exploiting the auxiliary task of action-conditioned future prediction.
September 2016
Learning image representations tied to ego-motion
An agent's continuous visual observations include information about how the world responds to its actions. This can provide an effective source of self-supervision for learning visual representations.
October 2015