activity
20152021
most citedGeneralized Grounding Graphs: A Probabilistic Framework for Understanding Grounded Commands

23 citations · 51 across the 9 of their papers we have counts for

collaborators

15 papers

cs.RO20217 cited

Grasp and Motion Planning for Dexterous Manipulation for the Real Robot Challenge

Takuma Yoneda, Charles Schaff, Takahiro Maeda +1

This report describes our winning submission to the Real Robot Challenge (https://real-robot-challenge.com/). The Real Robot Challenge is a three-phase dexterous manipulation compe…

cs.CL2020

Pow-Wow: A Dataset and Study on Collaborative Communication in Pommerman

Takuma Yoneda, Matthew R. Walter, Jason Naradowsky

In multi-agent learning, agents must coordinate with each other in order to succeed. For humans, this coordination is typically accomplished through the use of language. In this wo…

cs.RO20201 cited

Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents

Jacopo Tani, Andrea F. Daniele, Gianmarco Bernasconi +10

As robotics matures and increases in complexity, it is more necessary than ever that robot autonomy research be reproducible. Compared to other sciences, there are specific challen…

cs.LG2020

Concurrent Training Improves the Performance of Behavioral Cloning from Observation

Zachary W. Robertson, Matthew R. Walter

Learning from demonstration is widely used as an efficient way for robots to acquire new skills. However, it typically requires that demonstrations provide full access to the state…

cs.RO2020

Residual Policy Learning for Shared Autonomy

Charles Schaff, Matthew R. Walter

Shared autonomy provides an effective framework for human-robot collaboration that takes advantage of the complementary strengths of humans and robots to achieve common goals. Many…

cs.LG2020

Loop Estimator for Discounted Values in Markov Reward Processes

Falcon Z. Dai, Matthew R. Walter

At the working heart of policy iteration algorithms commonly used and studied in the discounted setting of reinforcement learning, the policy evaluation step estimates the value of…