The search for survivors: Cooperative human-robot interaction in search and rescue environments using semi-autonomous robots

Author(s):  
Barzin Doroodgar ◽  
Maurizio Ficocelli ◽  
Babak Mobedi ◽  
Goldie Nejat
AI Magazine ◽  
2015 ◽  
Vol 36 (3) ◽  
pp. 107-112
Author(s):  
Adam B. Cohen ◽  
Sonia Chernova ◽  
James Giordano ◽  
Frank Guerin ◽  
Kris Hauser ◽  
...  

The AAAI 2014 Fall Symposium Series was held Thursday through Saturday, November 13–15, at the Westin Arlington Gateway in Arlington, Virginia adjacent to Washington, DC. The titles of the seven symposia were Artificial Intelligence for Human-Robot Interaction, Energy Market Prediction, Expanding the Boundaries of Health Informatics Using AI, Knowledge, Skill, and Behavior Transfer in Autonomous Robots, Modeling Changing Perspectives: Reconceptualizing Sensorimotor Experiences, Natural Language Access to Big Data, and The Nature of Humans and Machines: A Multidisciplinary Discourse. The highlights of each symposium are presented in this report.


Author(s):  
Akimul Prince ◽  
Biswanath Samanta

The paper presents a control approach based on vertebrate neuromodulation and its implementation on an autonomous robot platform. A simple neural network is used to model the neuromodulatory function for generating context based behavioral responses to sensory signals. The neural network incorporates three types of neurons — cholinergic and noradrenergic (ACh/NE) neurons for attention focusing and action selection, dopaminergic (DA) neurons for curiosity-seeking, and serotonergic (5-HT) neurons for risk aversion behavior. The implementation of the neuronal model on a relatively simple autonomous robot illustrates its interesting behavior adapting to changes in the environment. The integration of neuromodulation based robots in the study of human-robot interaction would be worth considering in future.


Author(s):  
Fotios Papadopoulos ◽  
Kerstin Dautenhahn ◽  
Wan Ching Ho

AbstractThis article describes the design and evaluation of AIBOStory - a novel, remote interactive story telling system that allows users to create and share common stories through an integrated, autonomous robot companion acting as a social mediator between two remotely located people. The behaviour of the robot was inspired by dog behaviour, including a simple computational memory model. AIBOStory has been designed to work alongside online video communication software and aims to enrich remote communication experiences over the internet. An initial pilot study evaluated the proposed system’s use and acceptance by the users. Five pairs of participants were exposed to the system, with the robot acting as a social mediator, and the results suggested an overall positive acceptance response. The main study involved long-term interactions of 20 participants using AIBOStory in order to study their preferences between two modes: using the game enhanced with an autonomous robot and a non-robot mode which did not use the robot. Instruments used in this study include multiple questionnaires from different communication sessions, demographic forms and logged data from the robots and the system. The data was analysed using quantitative and qualitative techniques to measure user preference and human-robot interaction. The statistical analysis suggests user preferences towards the robot mode.


interactions ◽  
2005 ◽  
Vol 12 (2) ◽  
pp. 39-41 ◽  
Author(s):  
Jill L. Drury ◽  
Holly A. Yanco ◽  
Jean Scholtz

Author(s):  
Robin R. Murphy ◽  
Jennifer L. Burke

The Center for Robot-Assisted Search and Rescue has collected data at three responses (World Trade Center, Hurricane Charley, and the La Conchita mudslide) and nine high fidelity field exercises. Our results can be distilled into four lessons. First, building situation awareness, not autonomous navigation, is the major bottleneck in robot autonomy. Most of the robotics literature assumes a single operator single robot (SOSR), while our work shows that two operators working together are nine times more likely to find a victim. Second, human-robot interaction should not be thought of how to control the robot but rather how a team of experts can exploit the robot as an active information source. The third lesson is that team members use shared visual information to build shared mental models and facilitate team coordination. This suggests that high bandwidth, reliable communications will be necessary for effective teamwork. Fourth, victims and rescuers in close proximity to the robots respond to the robot socially. We conclude with observations about the general challenges in human-robot interaction.


2006 ◽  
Author(s):  
Jean Scholtz ◽  
Jeff Young ◽  
Holly A. Yanco ◽  
Jill L. Drury

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