Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113797
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Title: Interactive perception for deformable object manipulation
Authors: Weng, Z
Zhou, P 
Yin, H
Kravberg, A
Varava, A
NavarroAlarcon, D 
Kragic, D
Issue Date: Sep-2024
Source: IEEE robotics and automation letters, Sept 2024, v. 9, no. 9, p. 7763-7770
Abstract: Interactive perception enables robots to manipulate the environment and objects to bring them into states that benefit the perception process. Deformable objects pose challenges to this due to manipulation difficulty and occlusion in vision-based perception. In this work, we address such a problem with a setup involving both an active camera and an object manipulator. Our approach is based on a sequential decision-making framework and explicitly considers the motion regularity and structure in coupling the camera and manipulator. We contribute a method for constructing and computing a subspace, called Dynamic Active Vision Space (DAVS), for effectively utilizing the regularity in motion exploration. The effectiveness of the framework and approach are validated in both a simulation and a real dual-arm robot setup. Our results confirm the necessity of an active camera and coordinative motion in interactive perception for deformable objects.
Keywords: Manipulation planning
Perception for grasping and manipulation
Perception-action coupling
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE robotics and automation letters 
EISSN: 2377-3766
DOI: 10.1109/LRA.2024.3431943
Rights: © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The following publication Z. Weng et al., "Interactive Perception for Deformable Object Manipulation," in IEEE Robotics and Automation Letters, vol. 9, no. 9, pp. 7763-7770, Sept. 2024 is available at https://doi.org/10.1109/LRA.2024.3431943.
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