8 citations · 27 across the 14 of their papers we have counts for
14 papers
StackGen: Generating Stable Structures from Silhouettes via Diffusion
Luzhe Sun, Takuma Yoneda, Samuel W. Wheeler +2
Humans naturally obtain intuition about the interactions between and the stability of rigid objects by observing and interacting with the world. It is this intuition that governs t…
Generative Modeling Perspective for Control and Reasoning in Robotics
Takuma Yoneda
Heralded by the initial success in speech recognition and image classification, learning-based approaches with neural networks, commonly referred to as deep learning, have spread a…
6-DoF Stability Field via Diffusion Models
Takuma Yoneda, Tianchong Jiang, Gregory Shakhnarovich +1
A core capability for robot manipulation is reasoning over where and how to stably place objects in cluttered environments. Traditionally, robots have relied on object-specific, ha…
Cold Diffusion on the Replay Buffer: Learning to Plan from Known Good States
Zidan Wang, Takeru Oba, Takuma Yoneda +3
Learning from demonstrations (LfD) has successfully trained robots to exhibit remarkable generalization capabilities. However, many powerful imitation techniques do not prioritize…
Blending Imitation and Reinforcement Learning for Robust Policy Improvement
Xuefeng Liu, Takuma Yoneda, Rick L. Stevens +2
While reinforcement learning (RL) has shown promising performance, its sample complexity continues to be a substantial hurdle, restricting its broader application across a variety…
Statler: State-Maintaining Language Models for Embodied Reasoning
Takuma Yoneda, Jiading Fang, Peng Li +7
There has been a significant research interest in employing large language models to empower intelligent robots with complex reasoning. Existing work focuses on harnessing their ab…
Active Policy Improvement from Multiple Black-box Oracles
Xuefeng Liu, Takuma Yoneda, Chaoqi Wang +2
Reinforcement learning (RL) has made significant strides in various complex domains. However, identifying an effective policy via RL often necessitates extensive exploration. Imita…
To the Noise and Back: Diffusion for Shared Autonomy
Takuma Yoneda, Luzhe Sun, Ge Yang +2
Shared autonomy is an operational concept in which a user and an autonomous agent collaboratively control a robotic system. It provides a number of advantages over the extremes of…
Invariance Through Latent Alignment
Takuma Yoneda, Ge Yang, Matthew R. Walter +1
A robot's deployment environment often involves perceptual changes that differ from what it has experienced during training. Standard practices such as data augmentation attempt to…
Real Robot Challenge: A Robotics Competition in the Cloud
Stefan Bauer, Felix Widmaier, Manuel Wüthrich +39
Dexterous manipulation remains an open problem in robotics. To coordinate efforts of the research community towards tackling this problem, we propose a shared benchmark. We designe…
Benchmarking Structured Policies and Policy Optimization for Real-World Dexterous Object Manipulation
Niklas Funk, Charles Schaff, Rishabh Madan +10
Dexterous manipulation is a challenging and important problem in robotics. While data-driven methods are a promising approach, current benchmarks require simulation or extensive en…
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…
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…
Bib2vec: An Embedding-based Search System for Bibliographic Information
Takuma Yoneda, Koki Mori, Makoto Miwa +1
We propose a novel embedding model that represents relationships among several elements in bibliographic information with high representation ability and flexibility. Based on this…