  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.
