Semantic-based Loco-Manipulation for Human-Robot Collaboration in Industrial Environments
CoRR(2023)
摘要
Robots with a high level of autonomy are increasingly requested by smart
industries. A way to reduce the workers' stress and effort is to optimize the
working environment by taking advantage of autonomous collaborative robots. A
typical task for Human-Robot Collaboration (HRC) which improves the working
setup in an industrial environment is the \textit{"bring me an object please"}
where the user asks the collaborator to search for an object while he/she is
focused on something else. As often happens, science fiction is ahead of the
times, indeed, in the \textit{Iron Man} movie, the robot \textit{Dum-E} helps
its creator, \textit{Tony Stark}, to create its famous armours. The ability of
the robot to comprehend the semantics of the environment and engage with it is
valuable for the human execution of more intricate tasks. In this work, we
reproduce this operation to enable a mobile robot with manipulation and
grasping capabilities to leverage its geometric and semantic understanding of
the environment for the execution of the \textit{Bring Me} action, thereby
assisting a worker autonomously. Results are provided to validate the proposed
workflow in a simulated environment populated with objects and people. This
framework aims to take a step forward in assistive robotics autonomy for
industries and domestic environments.
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