Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Aronson, Reuben"'
Human-in-the-loop learning is gaining popularity, particularly in the field of robotics, because it leverages human knowledge about real-world tasks to facilitate agent learning. When people instruct robots, they naturally adapt their teaching behavi
Externí odkaz:
http://arxiv.org/abs/2409.09827
Users of shared control systems change their behavior in the presence of assistance, which conflicts with assumpts about user behavior that some assistance methods make. In this paper, we propose an analysis technique to evaluate the user's experienc
Externí odkaz:
http://arxiv.org/abs/2408.12103
Reinforcement Learning (RL) is an effective method for robots to learn tasks. However, in typical RL, end-users have little to no control over how the robot does the task after the robot has been deployed. To address this, we introduce the idea of on
Externí odkaz:
http://arxiv.org/abs/2408.16776
Foundation models are a promising path toward general-purpose and user-friendly robots. The prevalent approach involves training a generalist policy that, like a reinforcement learning policy, uses observations to output actions. Although this approa
Externí odkaz:
http://arxiv.org/abs/2407.08065
Enhancing the expressiveness of human teaching is vital for both improving robots' learning from humans and the human-teaching-robot experience. In this work, we characterize and test a little-used teaching signal: \textit{progress}, designed to repr
Externí odkaz:
http://arxiv.org/abs/2407.06459
It is crucial that users are empowered to take advantage of the functionality of a robot and use their understanding of that functionality to perform novel and creative tasks. Given a robot trained with Reinforcement Learning (RL), a user may wish to
Externí odkaz:
http://arxiv.org/abs/2406.13711
It is crucial that users are empowered to use the functionalities of a robot to creatively solve problems on the fly. A user who has access to a Reinforcement Learning (RL) based robot may want to use the robot's autonomy and their knowledge of its b
Externí odkaz:
http://arxiv.org/abs/2312.05991
Publikováno v:
IROS 2023
Learning from human feedback is an effective way to improve robotic learning in exploration-heavy tasks. Compared to the wide application of binary human feedback, scalar human feedback has been used less because it is believed to be noisy and unstab
Externí odkaz:
http://arxiv.org/abs/2311.10284
Autor:
Newman, Benjamin A., Aronson, Reuben M., Srinivasa, Siddartha S., Kitani, Kris, Admoni, Henny
We present the Human And Robot Multimodal Observations of Natural Interactive Collaboration (HARMONIC) data set. This is a large multimodal data set of human interactions with a robotic arm in a shared autonomy setting designed to imitate assistive e
Externí odkaz:
http://arxiv.org/abs/1807.11154
Autor:
Aronson, Reuben M
Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 47).
A clamping mechanism was designed for securing together two
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 47).
A clamping mechanism was designed for securing together two
Externí odkaz:
http://hdl.handle.net/1721.1/74426