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A Study of Human-Robot Interaction

In the contemporary world, tasks require robots to work in collaboration with humans in order to execute them. This process requires communication to synchronize events, collaborate, and portray the image of a team. The aforementioned statement requires the comprehension of human communication; although robots/agents experience the world from a different perspective.

Urban search and rescue provides illustrations that portray that the individual-robot team involves several individuals and one or several robots. The individuals in this team might be positioned tenuously or operate beside the robots in the hot zone. The teams are usually disseminated but the robots occupy the hot zone. The combined effort between the robots and the individuals occur in mutually skilled state whereby both parties’ skill offers the root of how strategies, activities and predictable outcomes are discretely understood (Lison et al, 140).

There are several fundamental necessities for transforming a robot into a team player. There is a general assumption that there exists no common foundation between humans and robots, each of them possesses their own perspective. The approach adopted in agent architecture is situational awareness. This approach embraces the procedure of buttressing and upholding an understanding of authenticity and the depiction of that understanding. Modeling a robot while complying with situational awareness enables a robot to understand and reason with strewn situational awareness. This approach creates a connection between probabilistic illustrations of familiarity and logical depictions of domain understanding. The latter enables robots to infer properties, existing engagements, and the probable consequences. Through the act of modeling the implications as beliefs, they can be ascribed to any number of team members (human or robot). Creating a link between the beliefs and experiences enables the positioning of robots in instances that confine them to what is achievable.

Moreover, the adoption of topological mapping construction equips the robot with a number of domain ontologies, connecting things, locations, and milestones to activities the robot can execute. When a robot encounters an ontological model, it derives further properties for that scenario. An exemplary illustration is a car in an accident. The robot can deduce that the vehicle has windows thus is more likely to have occupants. In such circumstances the robot checks for passengers. A recurring issue in the field of artificial intelligence is the capability to appropriately capture the social organization and utilize the subsequent model to circumnavigate and attain the objectives. The social behavior activity is founded on belief, desire, and intention model of human concrete thinking. The aforementioned model captures the complete social behavior band and offers design ideologies that permit robots to reason and transform their tendencies according to their individual insight of the compliant and modest natures of the community.

Communication within the individual-robot team entails more than mere comprehension of words. For a robot to comprehend what communication depicts, it has to understand the meaning behind the words. Communication in an individual-robot team is focused on task setting which is usually vastly monitored. Channel of communication in the above circumstance embraces a specific structure and applies a specific design. The conversations in this setup focus on the content conveyed, improving on precision and reducing uncertainty.

In an individual-robot team, the role one plays varies depending on one’s capabilities, ability to act under stress, and one’s autonomy. It is certain that robots cannot perform actions autonomously, and any attempt made to deployment of robotic systems which are autonomous will fall short of the objective. In simple terms, a robot’s autonomy varies, thus the roles assumed by such robots will occasionally shift. The aforementioned statement, affects the human’s roles and the overall team dynamics.

The sociological models embraced in human-robot teams postulate a band of social interpersonal behavior between the parties. First and foremost, the models suggest that robots have the ability of identifying themselves as members of a social group. Furthermore, every individual in the group possesses its own history, improvement configurations, and behavior outlines, that are portrayed in an individual’s summary to the degree they are recognized. Finally, there subsists mutual dependence that serves to be beneficial to the parties in the team (Burke, 39).

Conclusively, human beings tend to be socially competent but after extensive evolutionary process computational entities require an unequivocal means of demonstrating and perceptions about acts that possess social consequences.

Works Cited

Burke, Jennifer L. Moonlight in Miami: A Field Study of Human-Robot Interaction in the Context of an Urban Search and Rescue Disaster Response Training Exercise. Tampa, Fla.: University of South Florida, 2004.

Lison, P, C Ehrler, and G.-J.M Kruijff. “Belief Modelling for Situation Awareness in Human-Robot Interaction.” Proceedings – Ieee International Workshop on Robot and Human Interactive Communication. (2010): 138-143.