18,685 research outputs found
Towards robots reasoning about group behavior of museum visitors: leader detection and group tracking
The final publication is available at IOS Press through http://dx.doi.org/10.3233/AIS-170467Peer ReviewedPostprint (author's final draft
Show, Attend and Interact: Perceivable Human-Robot Social Interaction through Neural Attention Q-Network
For a safe, natural and effective human-robot social interaction, it is
essential to develop a system that allows a robot to demonstrate the
perceivable responsive behaviors to complex human behaviors. We introduce the
Multimodal Deep Attention Recurrent Q-Network using which the robot exhibits
human-like social interaction skills after 14 days of interacting with people
in an uncontrolled real world. Each and every day during the 14 days, the
system gathered robot interaction experiences with people through a
hit-and-trial method and then trained the MDARQN on these experiences using
end-to-end reinforcement learning approach. The results of interaction based
learning indicate that the robot has learned to respond to complex human
behaviors in a perceivable and socially acceptable manner.Comment: 7 pages, 5 figures, accepted by IEEE-RAS ICRA'1
Towards Assistive Feeding with a General-Purpose Mobile Manipulator
General-purpose mobile manipulators have the potential to serve as a
versatile form of assistive technology. However, their complexity creates
challenges, including the risk of being too difficult to use. We present a
proof-of-concept robotic system for assistive feeding that consists of a Willow
Garage PR2, a high-level web-based interface, and specialized autonomous
behaviors for scooping and feeding yogurt. As a step towards use by people with
disabilities, we evaluated our system with 5 able-bodied participants. All 5
successfully ate yogurt using the system and reported high rates of success for
the system's autonomous behaviors. Also, Henry Evans, a person with severe
quadriplegia, operated the system remotely to feed an able-bodied person. In
general, people who operated the system reported that it was easy to use,
including Henry. The feeding system also incorporates corrective actions
designed to be triggered either autonomously or by the user. In an offline
evaluation using data collected with the feeding system, a new version of our
multimodal anomaly detection system outperformed prior versions.Comment: This short 4-page paper was accepted and presented as a poster on
May. 16, 2016 in ICRA 2016 workshop on 'Human-Robot Interfaces for Enhanced
Physical Interactions' organized by Arash Ajoudani, Barkan Ugurlu, Panagiotis
Artemiadis, Jun Morimoto. It was peer reviewed by one reviewe
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