Robot Cooking With Stir-Fry: Bimanual Non-Prehensile Manipulation of Semi-Fluid Objects
نویسندگان
چکیده
This letter describes an approach to achieve well-known Chinese cooking art stir-fry on a bimanual robot system. Stir-fry requires sequence of highly dynamic coordinated movements, which is usually difficult learn for chef, let alone transfer robots. In this letter, we define canonical movement, and then propose decoupled framework learning deformable object manipulation from human demonstration. First, dualarms the are into different roles (a leader follower) learned with classical neural network based methods separately, task transformed coordination problem. To obtain general coordination, secondly Graph Transformer model— Structured-Transformer , capture spatio-temporal relationship between dual-arm movements. Finally, by adding visual feedback contents deformation, our can adjust movements automatically desired effect. We verify simulator deploy it real Panda The experimental results validate realize motion have potential extend other objects coordination.
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ژورنال
عنوان ژورنال: IEEE robotics and automation letters
سال: 2022
ISSN: ['2377-3766']
DOI: https://doi.org/10.1109/lra.2022.3153728