Previous work on assigning tasks to robots has proposed extensive categorizations of allocation of tasks with and without constraints. The main contribution of this paper is a specific categorization of problems that have temporal and ordering constraints. We propose a novel taxonomy that emphasizes the differences between temporal and ordering constraints, and organizes the current literature according to the nature of those constraints. We summarize widely used models and methods from the task allocation literature and related areas, such as vehicle routing and scheduling problems, showing similarities and differences.

The quantitative assessment of eye tracking data quality is critical for ensuring accuracy and precision of gaze position measurements. However, researchers often report the eye tracker’s optimal manufacturer’s specifications rather than empirical data about the accuracy and precision of the eye tracking data being presented. Indeed, a recent report indicates that less than half of eye tracking researchers surveyed take the eye tracker’s accuracy into account when determining areas of interest for analysis, an oversight that could impact the validity of reported results and conclusions. Accordingly, we designed a calibration verification protocol to augment independent quality assessment of eye tracking data and examined whether accuracy and precision varied between three age groups of participants. We also examined the degree to which our externally quantified quality assurance metrics aligned with those reported by the manufacturer. We collected data in standard laboratory conditions to demonstrate our method, to illustrate how data quality can vary with participant age, and to give a simple example of the degree to which data quality can differ from manufacturer reported values. In the sample data we collected, accuracy for adults was within the range advertised by the manufacturer, but for school-aged children, accuracy and precision measures were outside this range. Data from toddlers were less accurate and less precise than data from adults. Based on an a priori inclusion criterion, we determined that we could exclude approximately 20% of toddler participants for poor calibration quality quantified using our calibration assessment protocol. We recommend implementing and reporting quality assessment protocols for any eye tracking tasks with participants of any age or developmental ability. We conclude with general observations about our data, recommendations for what factors to consider when establishing data inclusion criteria, and suggestions for stimulus design that can help accommodate variability in calibration. The methods outlined here may be particularly useful for developmental psychologists who use eye tracking as a tool, but who are not experts in eye tracking per se. The calibration verification stimuli and data processing scripts that we developed, along with step-by-step instructions, are freely available for other researchers.

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We describe experiments performed with a large number of preschool children (ages 1.5 to 4 years) in a two-task eye tracking experiment and a human-robot interaction experiment. The resulting data of mostly neuro-typical children forms a baseline with which to compare children with autism, allowing us to further characterize the autism phenotype. Eye tracking task results indicate a strong preference for a humanoid robot and a social being (a four year old girl) over other robot types. Results from the human-robot interaction task, a semi-structured play interaction between child and robot, showed we can cluster participants based on social distances and other social responsiveness metrics.

Abstract. In this paper, we consider the problem of environmental constraints on teams and examine how the constraints impact teamwork. We simulate a realistic problem for teams in the physical world by implementing a limit on the range of communication among agents. Using BlocksWorld for Teams from Delft University of Technology, we build teams of 3-4 agents with varying communication ranges and of different agent type (regular task-performer, communication-only or reconnaissance-only) to test team performance in the constrained environment. We analyze the results and discuss implications to the team mental model. We show that adding a helper agent to the team can reduce task completion time, but not for all types of agents and environments.