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IROS 2025

Multi-Robot Assembly of Deformable Linear Objects Using Multi-Modal Perception

Conference Paper Accepted Paper Artificial Intelligence · Robotics

Abstract

Industrial assembly of deformable linear objects (DLOs) such as cables offers great potential for many industries. However, DLOs pose several challenges for robot-based automation due to the inherent complexity of deformation and, consequentially, the difficulties in anticipating the behavior of DLOs in dynamic situations. Although existing studies have addressed isolated subproblems like shape tracking, grasping, and shape control, there has been limited exploration of integrated workflows that combine these individual processes. To address this gap, we propose an object-centric perception and planning framework to achieve a comprehensive DLO assembly process throughout the industrial value chain. The framework utilizes visual and tactile information to track the DLO’s shape as well as contact state across different stages, which facilitates effective planning of robot actions. Our approach encompasses robot-based bin picking of DLOs from cluttered environments, followed by a coordinated handover to two additional robots that mount the DLOs onto designated fixtures. Real-World experiments employing a setup with multiple robots demonstrate the effectiveness of the approach and its relevance to industrial scenarios.

Authors

Keywords

  • Connectors
  • Service robots
  • Shape
  • Robot kinematics
  • Grasping
  • Handover
  • Robot sensing systems
  • Planning
  • Robots
  • Assembly
  • Deformable Objects
  • Multimodal Perception
  • Deformable Linear Objects
  • Assembly Process
  • Shape Control
  • Tactile Information
  • Multiple Robots
  • Local Information
  • Proprioceptive
  • Visual Perception
  • Workspace
  • Intersection Over Union
  • Global Estimates
  • Path Planning
  • Depth Images
  • Robotic Arm
  • Depth Camera
  • 3D Shape
  • Depth Data
  • Tactile Sensor
  • Instance Segmentation
  • Tangent Vector
  • Local Shape
  • Motion Primitives
  • Objects In Context
  • Global Shape
  • Foundation Model
  • Degrees Of Freedom

Context

Venue
IEEE/RSJ International Conference on Intelligent Robots and Systems
Archive span
1988-2025
Indexed papers
26578
Paper id
862633340950449489