18 citations · 27 across the 5 of their papers we have counts for
5 papers
Achieving Human Level Competitive Robot Table Tennis
David B. D'Ambrosio, Saminda Abeyruwan, Laura Graesser +24
Achieving human-level speed and performance on real world tasks is a north star for the robotics research community. This work takes a step towards that goal and presents the first…
Robotic Table Tennis: A Case Study into a High Speed Learning System
David B. D'Ambrosio, Jonathan Abelian, Saminda Abeyruwan +32
We present a deep-dive into a real-world robotic learning system that, in previous work, was shown to be capable of hundreds of table tennis rallies with a human and has the abilit…
Bi-Manual Block Assembly via Sim-to-Real Reinforcement Learning
Satoshi Kataoka, Youngseog Chung, Seyed Kamyar Seyed Ghasemipour +3
Most successes in robotic manipulation have been restricted to single-arm gripper robots, whose low dexterity limits the range of solvable tasks to pick-and-place, inser-tion, and…
Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning
Seyed Kamyar Seyed Ghasemipour, Daniel Freeman, Byron David +3
Assembly of multi-part physical structures is both a valuable end product for autonomous robotics, as well as a valuable diagnostic task for open-ended training of embodied intelli…
Bi-Manual Manipulation and Attachment via Sim-to-Real Reinforcement Learning
Satoshi Kataoka, Seyed Kamyar Seyed Ghasemipour, Daniel Freeman +1
Most successes in robotic manipulation have been restricted to single-arm robots, which limits the range of solvable tasks to pick-and-place, insertion, and objects rearrangement.…