To plan towards long-term goals through visual prediction, we propose a model based on two key ideas: (i) predict in a goal-conditioned way to restrict planning only to useful sequences, and (ii) recursively decompose the goal-conditioned prediction task into an increasingly fine series of subgoals.
Jun 1, 1010
How to train RL agents safely? We propose to pretrain a model-based agent in a mix of sandbox environments, then plan pessimistically when finetuning in the target environment.
Jun 1, 1010
We design and demonstrate a new tactile sensor for in-hand tactile manipulation in a robotic hand.
May 17, 17170
In visual prediction tasks, letting your predictive model choose which times to predict does two things: (i) improves prediction quality, and (ii) leads to semantically coherent "bottleneck state" predictions, which are useful for planning.
Jan 1, 1010
High-resolution tactile sensing together with visual approaches to prediction and planning with deep neural networks enables high-precision tactile servoing tasks.
Jan 1, 1010
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%.
Jan 1, 1010