19,245 research outputs found
Reusable Motivational Instruction Patterns for Socially Assistive Robots
Schneider S, Goerlich M, Kummert F. Reusable Motivational Instruction Patterns for Socially Assistive Robots. In: Workshop Towards Intelligent Social Robots ā Current Advances in Cognitive Robotics. https://intelligent-robots-ws.ensta-paristech.fr/?page_id=674; 2015
Humanoid Theory Grounding
In this paper we consider the importance of using a humanoid physical form for a certain proposed kind of robotics, that of theory grounding. Theory grounding involves grounding the theory skills and knowledge of an embodied artificially intelligent (AI) system by developing theory skills and knowledge from the bottom up. Theory grounding can potentially occur in a variety of domains, and the particular domain considered here is that of language. Language is taken to be another Āproblem spaceĀ in which a system can explore and discover solutions. We argue that because theory grounding necessitates robots experiencing domain information, certain behavioral-form aspects, such as abilities to socially smile, point, follow gaze, and generate manual gestures, are necessary for robots grounding a humanoid theory of language
Socially Assistive Robots as Decision Makers in the Wild: Insights from a Participatory Design Workshop
Socially Assistive Robots (SARs) are becoming very popular every day because
of their effectiveness in handling social situations. However, social robots
are perceived as intelligent, and thus their decision-making process might have
a significant effect on how they are perceived and how effective they are. In
this paper, we present the findings from a participatory design study
consisting of 5 design workshops with 30 participants, focusing on several
decision-making scenarios of SARs in the wild. Through the findings of the PD
study, we have discussed 5 directions that could aid the design of
decision-making systems of SARs in the wild.Comment: CHI Workshop on Socially Assistive Robots as Decision Makers:
Transparency, Motivations, and Intention
Socially Compliant Navigation Dataset (SCAND): A Large-Scale Dataset of Demonstrations for Social Navigation
Social navigation is the capability of an autonomous agent, such as a robot,
to navigate in a 'socially compliant' manner in the presence of other
intelligent agents such as humans. With the emergence of autonomously
navigating mobile robots in human populated environments (e.g., domestic
service robots in homes and restaurants and food delivery robots on public
sidewalks), incorporating socially compliant navigation behaviors on these
robots becomes critical to ensuring safe and comfortable human robot
coexistence. To address this challenge, imitation learning is a promising
framework, since it is easier for humans to demonstrate the task of social
navigation rather than to formulate reward functions that accurately capture
the complex multi objective setting of social navigation. The use of imitation
learning and inverse reinforcement learning to social navigation for mobile
robots, however, is currently hindered by a lack of large scale datasets that
capture socially compliant robot navigation demonstrations in the wild. To fill
this gap, we introduce Socially CompliAnt Navigation Dataset (SCAND) a large
scale, first person view dataset of socially compliant navigation
demonstrations. Our dataset contains 8.7 hours, 138 trajectories, 25 miles of
socially compliant, human teleoperated driving demonstrations that comprises
multi modal data streams including 3D lidar, joystick commands, odometry,
visual and inertial information, collected on two morphologically different
mobile robots a Boston Dynamics Spot and a Clearpath Jackal by four different
human demonstrators in both indoor and outdoor environments. We additionally
perform preliminary analysis and validation through real world robot
experiments and show that navigation policies learned by imitation learning on
SCAND generate socially compliant behavior
Overcoming barriers and increasing independence: service robots for elderly and disabled people
This paper discusses the potential for service robots to overcome barriers and increase independence of
elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly
people and advances in technology which will make new uses possible and provides suggestions for some of these new
applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses
the complementarity of assistive service robots and personal assistance and considers the types of applications and
users for which service robots are and are not suitable
The Contribution of Society to the Construction of Individual Intelligence
It is argued that society is a crucial factor in the construction of individual intelligence. In other words that it is important that intelligence is socially situated in an analogous way to the physical situation of robots. Evidence that this may be the case is taken from developmental linguistics, the social intelligence hypothesis, the complexity of society, the need for self-reflection and autism. The consequences for the development of artificial social agents is briefly considered. Finally some challenges for research into socially situated intelligence are highlighted
The Essence of Ethical Reasoning in Robot-Emotion Processing
Ā© 2017, Springer Science+Business Media B.V., part of Springer Nature. As social robots become more and more intelligent and autonomous in operation, it is extremely important to ensure that such robots act in socially acceptable manner. More specifically, if such an autonomous robot is capable of generating and expressing emotions of its own, it should also have an ability to reason if it is ethical to exhibit a particular emotional state in response to a surrounding event. Most existing computational models of emotion for social robots have focused on achieving a certain level of believability of the emotions expressed. We argue that believability of a robotās emotions, although crucially necessary, is not a sufficient quality to elicit socially acceptable emotions. Thus, we stress on the need of higher level of cognition in emotion processing mechanism which empowers social robots with an ability to decide if it is socially appropriate to express a particular emotion in a given context or it is better to inhibit such an experience. In this paper, we present the detailed mathematical explanation of the ethical reasoning mechanism in our computational model, EEGS, that helps a social robot to reach to the most socially acceptable emotional state when more than one emotions are elicited by an event. Experimental results show that ethical reasoning in EEGS helps in the generation of believable as well as socially acceptable emotions
- ā¦