Search Results for author:
Found 4 papers, 2 papers with code
A Touch, Vision, and Language Dataset for Multimodal Alignment
This is partially due to the difficulty of obtaining natural language labels for tactile data and the complexity of aligning tactile readings with both visual observations and language descriptions.
IIFL: Implicit Interactive Fleet Learning from Heterogeneous Human Supervisors
Imitation learning has been applied to a range of robotic tasks, but can struggle when robots encounter edge cases that are not represented in the training data (i. e., distribution shift).
Efficient Preference-Based Reinforcement Learning Using Learned Dynamics Models
In particular, we provide evidence that a learned dynamics model offers the following benefits when performing PbRL: (1) preference elicitation and policy optimization require significantly fewer environment interactions than model-free PbRL, (2) diverse preference queries can be synthesized safely and efficiently as a byproduct of standard model-based RL, and (3) reward pre-training based on suboptimal demonstrations can be performed without any environmental interaction.
Learning to Efficiently Plan Robust Frictional Multi-Object Grasps
In physical experiments, we find a 13. 7% increase in success rate, a 1. 6x increase in picks per hour, and a 6. 3x decrease in grasp planning time compared to prior work on multi-object grasping.
