To facilitate the advancement of research in healthcare robots without human intervention or commands, we introduce the Autonomous Helping Challenge, along with a crowd-sourcing large-scale dataset. The goal is to create healthcare robots that possess the ability to determine when assistance is necessary, generate useful sub-tasks to aid in planning, carry out these plans through a physical robot, and receive feedback from the environment in order to generate new tasks and continue the process. Besides the general challenge in open-ended scenarios, Autonomous Helping focuses on three specific challenges: autonomous task generation, the gap between the current scene and static commonsense, and the gap between language instruction and the real world. Additionally, we propose Helpy, a potential approach to close the healthcare loop in the learning-free setting.

翻译：为了推动无需人类干预或指令的医疗机器人研究进展，我们提出了自主帮助挑战（Autonomous Helping Challenge），并配套发布了一个大规模众包数据集。其目标是创建能够自主判断何时需要援助、生成有助于规划的有用子任务、通过实体机器人执行这些计划，并从环境中接收反馈以生成新任务并持续这一过程的医疗机器人。除开放式场景中的一般挑战外，自主帮助挑战重点聚焦三大特定挑战：自主任务生成、当前场景与静态常识之间的鸿沟，以及语言指令与现实世界之间的差距。此外，我们提出了Helpy——一种在无学习设定下实现医疗闭环的潜在方案。