An Evaluation of Human Mental Models of Tactical Robot Movement

Talone, Andrew B.; Phillips, Elizabeth; Ososky, Scott; Jentsch, Florian

doi:10.1177/1541931215591337

Cited by 5 publications

(4 citation statements)

References 16 publications

(15 reference statements)

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“…27 As previously mentioned, robots are transitioning from functional tools to interactive teammates. [28][29][30][31] Robust level of robot intelligence will cause HRI to evolve beyond command and control methods. Human mental models 30, 31 for human-robot teams dictate how humans expect a robot to plan and execute tactical movement commands under constraints like "navigate quickly", "navigate stealthily", and "navigate safely".…”

Section: Related Workmentioning

confidence: 99%

Interactive multi-objective path planning through a palette-based user interface

Shaikh

Goodrich

et al. 2016

SPIE Proceedings

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In a problem where a human uses supervisory control to manage robot path-planning, there are times when human does the path planning, and if satisfied commits those paths to be executed by the robot, and the robot executes that plan. In planning a path, the robot often uses an optimization algorithm that maximizes or minimizes an objective. When a human is assigned the task of path planning for robot, the human may care about multiple objectives. This work proposes a graphical user interface (GUI) designed for interactive robot path-planning when an operator may prefer one objective over others or care about how multiple objectives are traded off. The GUI represents multiple objectives using the metaphor of an artist's palette. A distinct color is used to represent each objective, and tradeoffs among objectives are balanced in a manner that an artist mixes colors to get the desired shade of color. Thus, human intent is analogous to the artist's shade of color. We call the GUI an "Adverb Palette" where the word "Adverb" represents a specific type of objective for the path, such as the adverbs "quickly" and "safely" in the commands: "travel the path quickly", "make the journey safely". The novel interactive interface provides the user an opportunity to evaluate various alternatives (that tradeoff between different objectives) by allowing her to visualize the instantaneous outcomes that result from her actions on the interface. In addition to assisting analysis of various solutions given by an optimization algorithm, the palette has additional feature of allowing the user to define and visualize her own paths, by means of waypoints (guiding locations) thereby spanning variety for planning. The goal of the Adverb Palette is thus to provide a way for the user and robot to find an acceptable solution even though they use very different representations of the problem. Subjective evaluations suggest that even non-experts in robotics can carry out the planning tasks with a great deal of flexibility using the adverb palette.

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Section: Related Workmentioning

confidence: 99%

Interactive multi-objective path planning through a palette-based user interface

Shaikh

Goodrich

et al. 2016

SPIE Proceedings

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“…Zweitens, indem sie oftmals Technologien sprachlich vermitteln und dabei mitunter Anwender adressieren, die über wenig Bezug zu moderner Technologie verfügen. Gerade solche Personen treten der Technologie mit wenig ausgebildeten, unterkomplexen mentalen Modellen und daraus abgeleiteten Erwartungshaltungen entgegen, die noch in hohem Maße instabil und gestaltbar sind [Tal+16]. Wirtschaftsinformatiker sind also häufig diejenigen, die durch die Gestaltung von Technologie als auch durch ihre Sprache über dieselbige entscheidend dazu beitragen, welches Bild bei den (späteren) Verwendern erzeugt wird.…”

Section: 4unclassified

Angewandte Forschung in der Wirtschaftsinformatik 2020 : Tagungsband zur 33. AKWI-Jahrestagung am 14.09.2020, ausgerichtet von der Hochschule Karlsruhe - Wirtschaft und Technik

2020

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“…But appropriate display of social cues is only half of the equation. Similarly if the social cues are robot provides are not easily understood, then humans observing the robot will be unable to discern its intention(s) or underlying goal(s) (Dragan, Lee, & Srinivasa, 2013;Talone, Phillips, Ososky, & Jentsch, 2015). Thus, it is important to understand how humans interpret the actions and behaviors of robots, especially those intended to function as teammates.…”

Section: Social Cognition In Human-robot Teamsmentioning

confidence: 99%

The Application and Extension of the Human-Animal Team Model to Better Understand Human-Robot Interaction: Recommendations for Further Research

Kapalo

Phillips

Fiore

2016

Proceedings of the Human Factors and Ergonomics Society Annual

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In order to create effective human-robot teams, robots must possess social capabilities that match the expectations of their human teammates. However the ability of robots to approximate human capacities is limited due to technological constraints. Human-animal teams have thus been suggested as a suitable analog for modeling teaming between humans and non-humans. Due to the limited capacity for animals to express their intentions, it follows that human-animal relationships can provide a basic framework for understanding how humans interpret information from teammates with limited social faculties. The purpose of this paper is provide research recommendations to identify specific areas in which human-animal teams can be used to model human-robot teams and to provide suggestions for investigating this model empirically in the context of social interaction.

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An Evaluation of Human Mental Models of Tactical Robot Movement

Cited by 5 publications

References 16 publications

Interactive multi-objective path planning through a palette-based user interface

Interactive multi-objective path planning through a palette-based user interface

Angewandte Forschung in der Wirtschaftsinformatik 2020 : Tagungsband zur 33. AKWI-Jahrestagung am 14.09.2020, ausgerichtet von der Hochschule Karlsruhe - Wirtschaft und Technik

The Application and Extension of the Human-Animal Team Model to Better Understand Human-Robot Interaction: Recommendations for Further Research

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