Our team, TRAIL, consists of AI/ML laboratory members from The University of Tokyo. We leverage our extensive research experience in state-of-the-art machine learning to build general-purpose in-home service robots. We previously participated in two competitions using Human Support Robot (HSR): RoboCup@Home Japan Open 2020 (DSPL) and World Robot Summit 2020, equivalent to RoboCup World Tournament. Throughout the competitions, we showed that a data-driven approach is effective for performing in-home tasks. Aiming for further development of building a versatile and fast-adaptable system, in RoboCup @Home 2023, we unify three technologies that have recently been evaluated as components in the fields of deep learning and robot learning into a real household robot system. In addition, to stimulate research all over the RoboCup@Home community, we build a platform that manages data collected from each site belonging to the community around the world, taking advantage of the characteristics of the community.

翻译：我们的团队TRAIL由东京大学人工智能与机器学习实验室成员组成。我们利用在尖端机器学习领域的丰富研究经验，构建通用型家用服务机器人。此前，我们曾使用人类支持机器人（HSR）参加两次竞赛：2020年RoboCup@Home日本公开赛（DSPL）以及相当于RoboCup世界锦标赛的2020年世界机器人峰会。通过这两次竞赛，我们证明了数据驱动方法在完成室内任务中的有效性。为持续推进构建多功能且快速适应系统的研发目标，在2023年RoboCup@Home竞赛中，我们将深度学习与机器人学习领域近期已验证有效性的三项组件级技术整合至真实家庭机器人系统中。此外，为激发RoboCup@Home社区整体的研究活力，我们利用该社区的独特属性，构建了一个可管理全球各站点采集数据的平台。