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Human-inspired Grasping Strategies of Fresh Fruits and Vegetables Applied to Robotic Manipulation

Romeo Orsolino, Mykhaylo Marfeychuk, Mariana de Paula Assis Fonseca, Mario Baggetta, Wesley Wimshurst, Francesco Porta, Morgan Clarke, Giovanni Berselli, Jelizaveta Konstantinova

Abstract

Robotic manipulation of fresh fruits and vegetables, including the grasping of multiple loose items, has a strong industrial need but it still is a challenging task for robotic manipulation. This paper outlines the distinctive manipulation strategies used by humans to pick loose fruits and vegetables with the aim to better adopt them for robotic manipulation of diverse items. In this work we present a first version of a robotic setup designed to pick different single or multiple fresh items, featuring multi-fingered compliant robotic gripper. We analyse human grasping strategies from the perspective of industrial Key Performance Indicators (KPIs) used in the logistic sector. The robotic system was validated using the same KPIs, as well as taking into account human performance and strategies. This paper lays the foundation for future development of the robotic demonstrator for fresh fruit and vegetable intelligent manipulation, and outlines the need for generic approaches to handle the complexity of the task.

Human-inspired Grasping Strategies of Fresh Fruits and Vegetables Applied to Robotic Manipulation

Abstract

Robotic manipulation of fresh fruits and vegetables, including the grasping of multiple loose items, has a strong industrial need but it still is a challenging task for robotic manipulation. This paper outlines the distinctive manipulation strategies used by humans to pick loose fruits and vegetables with the aim to better adopt them for robotic manipulation of diverse items. In this work we present a first version of a robotic setup designed to pick different single or multiple fresh items, featuring multi-fingered compliant robotic gripper. We analyse human grasping strategies from the perspective of industrial Key Performance Indicators (KPIs) used in the logistic sector. The robotic system was validated using the same KPIs, as well as taking into account human performance and strategies. This paper lays the foundation for future development of the robotic demonstrator for fresh fruit and vegetable intelligent manipulation, and outlines the need for generic approaches to handle the complexity of the task.

Paper Structure

This paper contains 13 sections, 9 figures, 2 tables.

Figures (9)

  • Figure 1: Samples of human grasp benchmark picking brussel sprounts (top), shallot onions (middle) and large strawberries (bottom). Our analysis included other fresh and loose products of small and large size such as sweet peppers, mandarins, button mushrooms, baby carrots and plum tomatoes.
  • Figure 2: Number of picks and item type comparison for natural and single picks.
  • Figure 3: Mechanical design of the gripper, showing the kinematic joints of a single finger ($p_{1,n}$, $p_{2,n}$, $p_{3,n}$, $p_{4,n}$, $p_{5,n}$, with $n=1$ for the first finger, $n=2$ for the second, etc., in green), its degrees of actuation ($a_1$, $a_{2,n}$ for $n=1,2,3,4$, in red), the gear mechanism coupling the adduction degrees of freedom ($p_{1,n}$) of the four fingers, and the routing of the actuation cables.
  • Figure 4: Possible gripping configurations of the gripper: parallel (left image) and spherical (right image). All intermediate positions between the two represented configurations are also possible.
  • Figure 5: Behavior of the gripper's finger depending on the point of force application. If gripping using only the fingertip, the finger structure will behave like a rigid four-bar linkage (left image). If multiple objects are to be grasped, resulting in contact with the belt, the finger will exhibit flexible behavior and the fingertip will tend to close on the grip (right image).
  • ...and 4 more figures