Search for: All records

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. 

Cleaning work is a labor-intensive job that frequently exposes workers to substantial occupational hazards. Unfortunately, the outbreak of coronavirus disease 2019 (COVID-19) has increased the pressure on janitors and cleaners to meet the rising need for a safe and hygienic environment, particularly in grocery stores, where the majority of people get their daily necessities. To reduce the occupational hazards and fulfill the new challenges of COVID-19, autonomous cleaning robots, have been designed to complement human workers. However, a lack of understanding of the new generation of cleaning tools’ acceptance may raise safety concerns when they’re deployed. Therefore, a video-based survey was developed and distributed to 32 participants, aiming to assess human acceptance of the cleaning robot in grocery environments during the COVID-19 pandemic. Moreover, the effects of four factors (gender, work experience, knowledge, and pet) that may influence human acceptance of the cleaning robot were also examined. In general, our findings revealed a non-negative human acceptance of the cleaning robot, which is a positive sign of deploying cleaning robots in grocery stores to reduce the workload of employees and decrease COIVID-related anxiety and safety concerns of customers. Furthermore, prior knowledge of robotics was observed to have a significant effect on participants’ acceptance of the cleaning robot ( p = 0.039).