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Abstract As technology advances, Human-Robot Interaction (HRI) is boosting overall system efficiency and productivity. However, allowing robots to be present closely with humans will inevitably put higher demands on precise human motion tracking and prediction. Datasets that contain both humans and robots operating in the shared space are receiving growing attention as they may facilitate a variety of robotics and human-systems research. Datasets that track HRI with rich information other than video images during daily activities are rarely seen. In this paper, we introduce a novel dataset that focuses on social navigation between humans and robots in a future-oriented Wholesale and Retail Trade (WRT) environment (https://uf-retail-cobot-dataset.github.io/). Eight participants performed the tasks that are commonly undertaken by consumers and retail workers. More than 260 minutes of data were collected, including robot and human trajectories, human full-body motion capture, eye gaze directions, and other contextual information. Comprehensive descriptions of each category of data stream, as well as potential use cases are included. Furthermore, analysis with multiple data sources and future directions are discussed. 

Recent years have seen a rapid increase in drone usage in both commercial and personal use, due to recent changes in guidelines by the Federal Aviation Administration (FAA). In those guidelines, however, there seems to be very few requirements in terms of illumination requirements, apart from the need to use a visible strob ing anti-collision light for nighttime operations. Hence in this study, wereviewed existing LED illumination systems in off-the-shelf drones to determine what type of configurations they have and how is the LED illumination system generally used. We also introduced a customizable LED illumination system and tested it in a human in the loop study. Our p reliminary findings have revealed that the colors that are preferred by the participants did not match the most used colors in existing LED illumination systems in most off-the-shelf drones. We also observed a possible relationship between the color preferred and the weather conditions. 

With recent changes by the Federal Aviation Administration (FAA) opening the possibility of more areas for drones to be used, such as delivery, there will be increasingly more intera ctions between humans and drones soon. Although current human drone interaction (HDI) investigate what factors are necessary for safe interactions, very few has focused on drone illumination. Therefore, in this study, we explored how illumination affects users’ perception of the drone through a distance perception task. Data analysis did not indicate any significant effects in the normal distance estimation task for illumination or distance conditions. However, most participants underestimated the distance in the normal distance estimation task and indicated that the LED drone was closer when it wa s illuminated during the relative distance estimation task, even though the drones were equidistant. In future studies, factors such as the weather conditions, lighting patterns, and height of the drone will be explored.