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Estimating deformability of objects using meshless shape matching

Conference Paper Accepted Paper Artificial Intelligence · Robotics

Abstract

Humans interact with deformable objects on a daily basis but this still represents a challenge for robots. To enable manipulation of and interaction with deformable objects, robots need to be able to extract and learn the deformability of objects both prior to and during the interaction. Physics-based models are commonly used to predict the physical properties of deformable objects and simulate their deformation accurately. The most popular simulation techniques are force-based models that need force measurements. In this paper, we explore the applicability of a geometry-based simulation method called meshless shape matching (MSM) for estimating the deformability of objects. The main advantages of MSM are its controllability and computational efficiency that make it popular in computer graphics to simulate complex interactions of multiple objects at the same time. Additionally, a useful feature of the MSM that differentiates it from other physics-based simulation is to be independent of force measurements that may not be available to a robotic framework lacking force/torque sensors. In this work, we design a method to estimate deformability based on certain properties, such as volume conservation. Using the finite element method (FEM) we create the ground truth deformability for various settings to evaluate our method. The experimental evaluation shows that our approach is able to accurately identify the deformability of test objects, supporting the value of MSM for robotic applications.

Authors

Keywords

  • Shape
  • Deformable models
  • Strain
  • Finite element analysis
  • Computational modeling
  • Robots
  • Sensors
  • Finite Element Method
  • Force Measurements
  • Object Properties
  • Computer Graphics
  • Deformable Objects
  • Volume Conservation
  • Running Time
  • Transformation Matrix
  • Consistent Estimates
  • Object Shape
  • Model Resolution
  • Rigid Transformation
  • Tactile Sensor
  • Small Standard Deviation
  • Linear Elasticity
  • Deformation Model
  • Compression Rate
  • Translation Vector
  • Deformation Parameters
  • Finite Element Method Model
  • Real-world Observations
  • Simulated Deformation
  • Linear Deformation
  • Force Information
  • Deformation Properties
  • Model Parameter Space

Context

Venue
IEEE/RSJ International Conference on Intelligent Robots and Systems
Archive span
1988-2025
Indexed papers
26578
Paper id
640971399676494571
v2026.09.13