Alexander Hubers

Leo Bowen-Biggs, Suzanne Dazo, Yili Zhang et al.

Maps --- specifically floor plans --- are useful for a variety of tasks from arranging furniture to designating conceptual or functional spaces (e.g., kitchen, walkway). We present a simple algorithm for quickly laying a floor plan (or other conceptual map) onto a SLAM map, creating a one-to-one mapping between them. Our goal was to enable using a floor plan (or other hand-drawn or annotated map) in robotic applications instead of the typical SLAM map created by the robot. We look at two use cases, specifying "no-go" regions within a room and locating objects within a scanned room. Although a user study showed no statistical difference between the two types of maps in terms of performance on this spatial memory task, we argue that floor plans are closer to the mental maps people would naturally draw to characterize spaces.

Alexander Hubers, Emily Andrulis, Levi Scott et al.

Systems that give control of a mobile robot to a remote user raise privacy concerns about what the remote user can see and do through the robot. We aim to preserve some of that privacy by manipulating the video data that the remote user sees. Through two user studies, we explore the effectiveness of different video manipulation techniques at providing different types of privacy. We simultaneously examine task performance in the presence of privacy protection. In the first study, participants were asked to watch a video captured by a robot exploring an office environment and to complete a series of observational tasks under differing video manipulation conditions. Our results show that using manipulations of the video stream can lead to fewer privacy violations for different privacy types. Through a second user study, it was demonstrated that these privacy-protecting techniques were effective without diminishing the task performance of the remote user.