![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() by Staff Writers Beijing, China (SPX) Jan 02, 2018
Robots have a lot to learn about humans, including how to respect their personal space. Scientists at the Institute of Automatics of the National University of San Juan in Argentina are giving mobile robots a crash course in avoiding collisions with humans. The researchers published their methods in IEEE/CAA Journal of Automatica Sinica (JAS), a joint publication of the IEEE and Chinese Association of Automation. "Humans respect social zones during different kind[s] of interactions," wrote Daniel Herrera, a postdoctoral researcher at the Institute of Automatics of the National University of San Juan and an author on the study. He notes how the specifics of a task and situation, as well as cultural expectations and personal preferences, influence the distance of social zones. "When a robot follows a human as part of a formation, it is supposed that it must also respect these social zones to improve its social acceptance." Using impedance control, the researchers aimed to regulate the social dynamics between the robot's movements and the interactions of the robot's environment. They did this by first analyzing how a human leader and a human follower interact on a set track with well-defined borders. The feedback humans use to adjust their behaviors - letting someone know they're following too closely, for example - was marked as social forces and treated as defined physical fields. The human interactions (leading and following), including the estimated social forces, were fed to a mobile robot. The programmed robot then followed the human within the same defined borders, but without impeding on the social forces defined by the human interactions. "Under the hypothesis that moving like human will be acceptable by humans, it is believed that the proposed control improves the social acceptance of the robot for this kind of interaction," wrote Herrera. The researchers posit that robots are more likely to be accepted if they can be programmed to respect and respond like humans in social interactions. In this experiment, the robot mimicked the following human, and avoided the leader's personal space. "The results show that the robot is capable of emulating the previously identified impedance and, consequently, it is believed that the proposed control can improve the social acceptance by being able to imitate this human-human dynamic behavior."
![]() Tokyo, Japan (SPX) Dec 15, 2017 Lockheed Martin and NEC Corp have announced that Lockheed Martin will use NEC's System Invariant Analysis Technology (SIAT) in the space domain. SIAT's advanced analytics engine uses data collected from sensors to learn the behavior of systems, including computer systems, power plants, factories and buildings, enabling the system itself to automatically detect inconsistencies and prescribe resol ... read more Related Links Chinese Association of Automation All about the robots on Earth and beyond!
![]()
![]() |
|
The content herein, unless otherwise known to be public domain, are Copyright 1995-2024 - Space Media Network. All websites are published in Australia and are solely subject to Australian law and governed by Fair Use principals for news reporting and research purposes. AFP, UPI and IANS news wire stories are copyright Agence France-Presse, United Press International and Indo-Asia News Service. ESA news reports are copyright European Space Agency. All NASA sourced material is public domain. Additional copyrights may apply in whole or part to other bona fide parties. All articles labeled "by Staff Writers" include reports supplied to Space Media Network by industry news wires, PR agencies, corporate press officers and the like. Such articles are individually curated and edited by Space Media Network staff on the basis of the report's information value to our industry and professional readership. Advertising does not imply endorsement, agreement or approval of any opinions, statements or information provided by Space Media Network on any Web page published or hosted by Space Media Network. General Data Protection Regulation (GDPR) Statement Our advertisers use various cookies and the like to deliver the best ad banner available at one time. All network advertising suppliers have GDPR policies (Legitimate Interest) that conform with EU regulations for data collection. By using our websites you consent to cookie based advertising. If you do not agree with this then you must stop using the websites from May 25, 2018. Privacy Statement. Additional information can be found here at About Us. |