PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
September 10, 2025Frontiers in Robotics and AI1 citationsOpen Access

Parametric modeling of deformable linear objects for robotic outfitting and maintenance of space systems

View Full Paper
AQAmy QuartaroJMJoshua MoserJCJ. R. Cooper

Key Points

  • Cable configuration modeling significantly reduces prediction errors in robotic applications, enhancing accuracy in space operations.
  • A model-based optimization approach employs parameter estimation to refine cable configuration predictions, improving modeling efficiency.
  • Applying this method reduces the size of the state space for cable manipulations, considering non-zero equilibrium states for accurate predictions.
  • The study emphasizes the importance of robotic agents in performing outfitting and maintenance of complex space systems.

Abstract

Outfitting and maintenance are important to an in-space architecture consisting of long duration missions. During such missions, crew is not continuously present; robotic agents become essential to the construction, maintenance, and servicing of complicated space assets, requiring some degree of autonomy to plan and execute tasks. There has been significant research into manipulation planning for rigid elements for in-space assembly and servicing, but flexible electrical cables, which fall under the domain of Deformable Linear Objects (DLOs), have not received such attention despite being critical components of powered space systems. Cables often have a non-zero bend equilibrium configuration, which the majority of DLO research does not consider. This article implements a model-based optimization approach to estimate cable configuration, where a design parameter of the model’s discretization level enables trading model accuracy vs computational complexity. Observed 2D cable configurations are used to improve the model via parameter estimation. The parameter estimation is validated through comparing predicted configurations based on estimated parameters to that of a real cable. The incorporation of parameter estimation to the cable model is shown to reduce prediction errors by an order of magnitude. The results of this work demonstrate some of the challenges present with robotic cable manipulation, exploring the complexities of outfitting and maintenance operations of in-space facilities, and puts forth a method for reducing the size of the state space of a cable payload while accounting for non-zero equilibrium configurations.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Quartaro et al. (2025) studied this question.

synapsesocial.com/papers/68c1ae7054b1d3bfb60e635dhttps://doi.org/10.3389/frobt.2025.1565837
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Robotic perception and manipulation of deformable linear objects: A survey2026 · 2 citations
  2. 2Shape Control of Elastic Deformable Linear Objects for Robotic Cable Assembly2024 · 3 citations
  3. 3Differentiable Discrete Elastic Rods for Real-Time Modeling of Deformable Linear Objects2024
  4. 4Model-based Manipulation of Deformable Objects with Non-negligible Dynamics as Shape Regulation2024
  5. 5Design and Nonlinear Modeling of a Modular Cable-Driven Soft Robotic Arm2024 · 2 citations