337 citations · 565 across the 11 of their papers we have counts for
7 papers · 1 filter
Implicit Behavioral Cloning
Pete Florence, Corey Lynch, Andy Zeng +7
We find that across a wide range of robot policy learning scenarios, treating supervised policy learning with an implicit model generally performs better, on average, than commonly…
Learning to See before Learning to Act: Visual Pre-training for Manipulation
Lin Yen-Chen, Andy Zeng, Shuran Song +2
Does having visual priors (e.g. the ability to detect objects) facilitate learning to perform vision-based manipulation (e.g. picking up objects)? We study this problem under the f…
Spatial Action Maps for Mobile Manipulation
Jimmy Wu, Xingyuan Sun, Andy Zeng +4
Typical end-to-end formulations for learning robotic navigation involve predicting a small set of steering command actions (e.g., step forward, turn left, turn right, etc.) from im…
Form2Fit: Learning Shape Priors for Generalizable Assembly from Disassembly
Kevin Zakka, Andy Zeng, Johnny Lee +1
Is it possible to learn policies for robotic assembly that can generalize to new objects? We explore this idea in the context of the kit assembly task. Since classic methods rely h…
DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions
Zhenjia Xu, Jiajun Wu, Andy Zeng +2
We study the problem of learning physical object representations for robot manipulation. Understanding object physics is critical for successful object manipulation, but also chall…
TossingBot: Learning to Throw Arbitrary Objects with Residual Physics
Andy Zeng, Shuran Song, Johnny Lee +2
We investigate whether a robot arm can learn to pick and throw arbitrary objects into selected boxes quickly and accurately. Throwing has the potential to increase the physical rea…