Semantic failure analysis improves handling of deformable objects
The Language of Deformation: Semantic Failure Analysis as a Prerequisite for Dexterous Manipulation of Deformable Objects
Robotics
Summary
Handling soft or bendy objects like cables and cloth is much harder for robots than handling hard, solid objects. The paper argues that understanding specific types of failures—like tearing or buckling—is essential before robots can skillfully manipulate these items. The authors define the main challenges of identifying these failures and show experiments that support this approach as a useful research direction.
What this means in practice
- •For robotics engineers: Develop more reliable robot control methods for handling flexible objects by detecting specific failure types during manipulation.
- •For manufacturing automation teams: Improve automation of deformable object handling in production lines by using semantic failure insights to reduce errors and improve quality control.
Authors
Ignacio Cuiral-Zueco, David Hardman, Michele Pierallini, Erfan Shahriari
Abstract
Dexterous manipulation of rigid objects has reached a level of maturity where grasp stability, control, and planning strategies are successfully applied in industry and logistics. In contrast, manipulating deformable objects (cables, plastic pieces, cloth) remains far more challenging, as rigid-object methods do not account for their additional complexity. This paper identifies semantic failure analysis as a key step toward mature deformable-object manipulation and supports this claim with proof-of-concept experiments. Unlike rigid-object manipulation, where goals are well-defined in terms of criteria such as force balance and slippage, deformable-object manipulation involves a broader variety of failure modes arising from differences in materials, geometry, and behaviour. Typical failures include buckling, plastic deformation, pressure variations, and tearing. These diverse and often hard-to-detect events require distinct corrective strategies, making semantic failure analysis necessary. We define its key components and challenges and present experimental results supporting its potential as a research direction.