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Abstract-In this work, we further test the hypothesis that physical embodiment has a measurable effect on performance and impression of social interactions. Support for this hypothesis would suggest fundamental differences between virtual agents and robots from a social standpoint and would have significant implications for human-robot interaction.We have refined our task-based metrics to give a measurement, not only of the participant's immediate impressions of a coach for a task, but also of the participant's performance in a given task. We measure task performance and participants' impression of a robot's social abilities in a structured task based on the Towers of Hanoi puzzle. Our experiment compares aspects of embodiment by evaluating: (1) the difference between a physical robot and a simulated one; and (2) the effect of physical presence through a co-located robot versus a remote, tele-present robot.With a participant pool (n=21) of roboticists and nonroboticists, we were able to show that participants felt that an embodied robot was more appealing and perceptive of the world than non-embodied robots. A larger pool of participants (n=32) also demonstrated that the embodied robot was seen as most helpful, watchful, and enjoyable when compared to a remote tele-present robot and a simulated robot.

Abstract-Physical interference limits the utility of largescale multi-robot systems. We present an empirical study of the effects of such interference in systems with hundreds of minimalist robots. We consider the canonical multi-robot foraging task, and define a new parametrized controller. This controller allows for evaluation of spatial arbitration strategies along a continuum with the traditional homogeneous and bucket-brigading algorithms at each end. We present data from thousands of simulations which suggests that methods surprisingly close to homogeneous foraging, but augmented with limited arbitration, can improve both performance and reliability.

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The beginning and development of modern intelligent robot makes robot task become more and more complicated. Task distribution and deployment for large-scale robots has become a major problem. Traditional distribution mechanisms are mainly Polling, SMS Push and IP Push, but for the task distribution of robotic devices, these mechanisms cannot fully meet the system's requirements. In this paper, we propose a "Push-Pull" distribution mechanism, and make a comparative experiment with the "Direct-Push" distribution mechanism based on MQTT protocol. Meanwhile, we construct a large-scale distribution and deployment system of robot task, which implements the distribution and deployment of large text tasks promptly and can guarantee the quality of task distribution. The experimental results show that the task package distributed by our system can run successfully on the robot operating system (ROS).

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Abstract-We consider the problem of multi-robot taskallocation when robots have to deal with uncertain utility estimates. Typically an allocation is performed to maximize expected utility; we consider a means for measuring the robustness of a given optimal allocation when robots have some measure of the uncertainty (e.g., a probability distribution, or moments of such distributions). We introduce a new O(n 4 ) algorithm, the Interval Hungarian algorithm, that extends the classic KuhnMunkres Hungarian algorithm to compute the maximum interval of deviation (for each entry in the assignment matrix) which will retain the same optimal assignment. This provides an efficient measurement of the tolerance of the allocation to the uncertainties, for both a specific interval and a set of interrelated intervals. We conduct experiments both in simulation and with physical robots to validate the approach and to gain insight into the effect of location uncertainty on allocations for multi-robot multi-target navigation tasks.