Learning Failure Prevention Skills for Safe Robot Manipulation

Abdullah Cihan Ak*, Eren Erdal Aksoy, Sanem Sariel

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Özet

Robots are more capable of achieving manipulation tasks for everyday activities than before. However, the safety of manipulation skills that robots employ is still an open problem. Considering all possible failures during skill learning increases the complexity of the process and restrains learning an optimal policy. Nonetheless, safety-focused modularity in the acquisition of skills has not been adequately addressed in previous works. For that purpose, we reformulate skills as base and failure prevention skills, where base skills aim at completing tasks and failure prevention skills aim at reducing the risk of failures to occur. Then, we propose a modular and hierarchical method for safe robot manipulation by augmenting base skills by learning failure prevention skills with reinforcement learning and forming a skill library to address different safety risks. Furthermore, a skill selection policy that considers estimated risks is used for the robot to select the best control policy for safe manipulation. Our experiments show that the proposed method achieves the given goal while ensuring safety by preventing failures. We also show that with the proposed method, skill learning is feasible and our safe manipulation tools can be transferred to the real environment.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)7994-8001
Sayfa sayısı8
DergiIEEE Robotics and Automation Letters
Hacim8
Basın numarası12
DOI'lar
Yayın durumuYayınlandı - 1 Ara 2023

Bibliyografik not

Publisher Copyright:
© 2016 IEEE.

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