Goto

Collaborating Authors

International Robot Exhibition 2017

USATODAY - Tech Top Stories

Toyota's third-generation humanoid T-HR3 robot is remotely controlled by a an employee at the International Robot Exhibition in Tokyo on Nov. 29, 2017.



Highlights From the International Robot Exhibition 2013

AITopics Original Links

The theme for this year's International Robot Exhibition (IREX) in Tokyo was "Making a Future with Robot." We're not exactly sure what that means, but we're definitely in favor of it, and here are some of the coolest things that we saw. There's one caveat with our IREX coverage, and that's the fact that there was a bit of a language barrier going on most of the time. With the exception of some big international robotics companies, there simply wasn't a lot of information available on many of the robots that we saw. We're following up as best we can, but in the meantime, enjoy this highlight video and gallery that we've put together for you.


Systems of natural-language-facilitated human-robot cooperation: A review

arXiv.org Artificial Intelligence

Natural-language-facilitated human-robot cooperation (NLC), in which natural language (NL) is used to share knowledge between a human and a robot for conducting intuitive human-robot cooperation (HRC), is continuously developing in the recent decade. Currently, NLC is used in several robotic domains such as manufacturing, daily assistance and health caregiving. It is necessary to summarize current NLC-based robotic systems and discuss the future developing trends, providing helpful information for future NLC research. In this review, we first analyzed the driving forces behind the NLC research. Regarding to a robot s cognition level during the cooperation, the NLC implementations then were categorized into four types {NL-based control, NL-based robot training, NL-based task execution, NL-based social companion} for comparison and discussion. Last based on our perspective and comprehensive paper review, the future research trends were discussed.


Estimating People's Subjective Experiences of Robot Behavior

AAAI Conferences

Progress in general HRI metrics, while significant, is often in the form of post-experiment questionnaires or expert video analysis. This is a significant hurdle for any intelligent system that aspires to interact with its social environment. In the case of social navigation, robots must react to a dynamic environment. Socially aware robot behavior requires real time quantitative metrics of human subjective experience. This is a vast topic, which we approach by trying to measure how predictable robot actions are from its impact on the paths taken by passers-by. We chose predictability as a first metric because it can be modelled in terms of efficiency, and it affects safety. Thus, it serves as an interesting proof of concept.