We present a survey of recent work on robot manipulation and sensing of deformable objects, a field with relevant applications in diverse industries such as medical (e.g. surgery assistance), food handling, manufacturing, and domestic chores (e.g. folding clothes). We classify the reviewed approaches into four categories based on the type of object they manipulate. Furthermore, within this object classification we divide the approaches based on the particular task they perform on the deformable object. Finally, we conclude this survey with a discussion of the current state of the art and propose future directions within the proposed classification.

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Robotic manipulation and sensing of deformable objects in domestic and industrial applications: a survey:

Probability analysis for grasp planning facing the field of medical robotics

Manipulation of deformable objects has given rise to an important set of open problems in the field of robotics. Application areas include robotic surgery, household robotics, manufacturing, logistics, and agriculture, to name a few. Related research problems span modeling and estimation of an object's shape, estimation of an object's material properties, such as elasticity and plasticity, object tracking and state estimation during manipulation, and manipulation planning and control. In this survey article, we start by providing a tutorial on foundational aspects of models of shape and shape dynamics. We then use this as the basis for a review of existing work on learning and estimation of these models and on motion planning and control to achieve desired deformations. We also discuss potential future lines of work.

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Modeling of Deformable Objects for Robotic Manipulation: A Tutorial and Review

https://hal.archives-ouvertes.fr/hal-01655448/document

Model-based strategy for grasping 3D deformable objects using a multi-fingered robotic hand

Multi-Modal Sensing and Robotic Manipulation of Non-Rigid Objects: A Survey

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Experiences on using Arduino for laboratory experiments of Automatic Control and Robotics

Grasping and manipulating deformable objects with a robot hand has several interesting challenges. Deformable objects, due to its texture and deformability, present different features from rigid ones and that issue can cause uncontrolled movements during grasping and/or manipulation. The paper presents a control strategy for grasping deformable objects, focused on elastic foams, based on tactile information. An adaptation at different elastic properties of the object is achieved, because the deformability degree is estimated during the grasping process. Several experiments are shown in order to demonstrate the reliability of the tactile-based strategy.

A tactile-based grasping strategy for deformable objects' manipulation and deformability estimation

Most works in dexterous manipulation consider Force Closure Grasp (FCG), not only for rigid object but also, for flexible ones, though in the second case a force readjustment is also necessary. However, there are situations in which FCG is nonviable. This paper deals with the situation of a flexible object that must be necessarily grasped from one of its sides, taking advantage of its flexibility. This situation is common in packaging processes, or other everyday situations carried out by people. The paper presents first a new solution based on a planner that reproduces the actions of a human hand, aided by a database with knowledge about previous tasks. The paper is focused on describing the first tests done to evaluate the effectiveness of the planner for grasping different basic flexible objects, compared to a human hand.

Study of dexterous robotic grasping for deformable objects manipulation

This paper presents a method to analyse 3D planar surfaces and to measure variations on it. The method is oriented to the detection of deformations on the elastic object surfaces formed by flat faces. These deformations are usually caused when two bodies, a solid and another elastic object, come in contact and there are contact pressures among their faces. Our method describes a strategy to model the shape of deformation using a mathematical approach based on two concepts: Histogram and Map of curvature. In particular, we describe the algorithm for deformations in order to use it in visual control and inspection tasks for manipulation processes with robot hands. Several experiments and their results are shown to evaluate the validity and robustness of the method to detect and measure deformations in grasping tasks. To do it, some virtual scenarios were created to simulate contacts with fingers of a hand robot.

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Analysis of shapes to measure surfaces: An approach for detection of deformations

This work was funded by Ministry of Economy and Competitiveness and supported by Spanish project (RTC-2014-1863-8).

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D. Mira

Papers

Experiences on using Arduino for laboratory experiments of Automatic Control and Robotics

A tactile-based grasping strategy for deformable objects' manipulation and deformability estimation

Study of dexterous robotic grasping for deformable objects manipulation

Analysis of shapes to measure surfaces: An approach for detection of deformations

Oil Spill Detection using Segmentation based Approaches