Interactive Perception for Deformable Object Manipulation

Zehang Weng, Peng Zhou, Hang Yin, Alexander Kravberg, Anastasiia Varava, David Navarro-Alarcon, Danica Kragic

Research output: Journal article publicationJournal articleAcademic researchpeer-review

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.

Original languageEnglish
Pages (from-to)7763-7770
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume9
Issue number9
DOIs
Publication statusPublished - Sept 2024

Keywords

  • Perception for grasping and manipulation
  • manipulation planning
  • perception-action coupling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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