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Interactive Perception for Deformable Object Manipulation

Zehang Weng, Peng Zhou, Hang Yin, A. I. Kravchenko, Anastasiia Varava, Danica Kragić

Year
2024
Citations
5

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

Object (grammar)PerceptionComputer scienceComputer visionHuman–computer interactionArtificial intelligenceComputer graphics (images)PsychologyCommunicationNeuroscience

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