Publication
Knowledge representation to enable high-level planning in cloth manipulation tasks
Conference Article
Conference
ICAPS Workshop on Knowledge Engineering for Planning and Scheduling (KEPS)
Edition
2022
Pages
9
Doc link
http://icaps22.icaps-conference.org/workshops/KEPS/KEPS-22_paper_2839.pdf
File
Abstract
Cloth manipulation is very relevant for domestic robotic tasks, but it presents many challenges due to the complexity of representing, recognizing and predicting the behaviour of cloth under manipulation. In this work, we propose a generic, compact and simplified representation of the states of cloth manipulation that allows for representing tasks as sequences of states and transitions semantically. We also define a Cloth Manipulation Graph that encodes all the strategies to accomplish a task. Our novel representation is used to encode two different cloth manipulation tasks, learned from an experiment with human subjects manipulating clothes with video data. We show how our simplified representation allows to obtain a map of meaningful steps that can serve to describe cloth manipulation tasks as domain models in PDDL, enabling high-level planning. Finally, we discuss on the existing skills that could enable the sensory motor grounding and the low-level execution of the plan.
Categories
knowledge engineering, planning (artificial intelligence).
Author keywords
Cloth manipulation, Knowledge representation
Scientific reference
I. Garcia-Camacho, J. Borràs and G. Alenyà. Knowledge representation to enable high-level planning in cloth manipulation tasks, 2022 ICAPS Workshop on Knowledge Engineering for Planning and Scheduling, 2022, Singapore (Virtual), pp. 9.
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