Search for: All records

Social telepresence robots (i.e., telerobots) are used for social and learning experiences by children. However, most (if not all) commercially available telerobot bodies were designed for adults in corporate or healthcare settings. Due to an adult-focused market, telerobot design has typically not considered important factors such as age and physical aspect in the design of robot bodies. To better understand how peer interactants can facilitate the identities of remote children through personalization of robot bodies, we conducted an exploratory study to evaluate collaborative robot personalization. In this study, child participants (N=28) attended an interactive lesson on robots in our society. After the lesson, participants interacted with two telerobots for personalization activities and a robot fashion show. Finally, participants completed an artwork activity on robot design. Initial findings from this study will inform our continued work on telepresence robots for virtual inclusion and improved educational experiences of remote children and their peers. 

We model the societal task of redistricting political districts as a partitioning problem: Given a set of n points in the plane, each belonging to one of two parties, and a parameter k, our goal is to compute a partition P of the plane into regions so that each region contains roughly s = n/k points. P should satisfy a notion of "local" fairness, which is related to the notion of core, a well-studied concept in cooperative game theory. A region is associated with the majority party in that region, and a point is unhappy in P if it belongs to the minority party. A group D of roughly s contiguous points is called a deviating group with respect to P if majority of points in D are unhappy in P. The partition P is locally fair if there is no deviating group with respect to P.This paper focuses on a restricted case when points lie in 1D. The problem is non-trivial even in this case. We consider both adversarial and "beyond worst-case" settings for this problem. For the former, we characterize the input parameters for which a locally fair partition always exists; we also show that a locally fair partition may not exist for certain parameters. We then consider input models where there are "runs" of red and blue points. For such clustered inputs, we show that a locally fair partition may not exist for certain values of s, but an approximate locally fair partition exists if we allow some regions to have smaller sizes. We finally present a polynomial-time algorithm for computing a locally fair partition if one exists.