# Automatic pre-grasps generation for unknown 3D objects

## TL;DR

This paper presents an automated method for generating pre-grasps on unknown 3D objects by decomposing objects into parts, encoding free faces, and checking grasp conditions, demonstrated on household objects.

## Contribution

The novel approach decomposes objects into primitive parts, encodes free faces, and systematically generates pre-grasps, improving grasp planning for unknown objects.

## Key findings

- Successfully applied on 24 household objects and toys.
- Generated grasps considering object part decomposition and face accessibility.
- Enhanced grasp planning accuracy with the proposed method.

## Abstract

In this paper, the problem of automating the pre-grasps generation for novel 3d objects has been discussed. The objects represented as cloud of 3D points are split into parts and organized in a tree structure, where parts are approximated by simple box primitives. Applying grasping only on the individual object parts may miss a good grasp which involves a combination of parts. The problem has been addressed by traversing the decomposition tree and checking each node of the tree for possible pre-grasps against a set of conditions. Further, a face mask has been introduced to encode the free and blocked faces of the box primitives. Pre-grasps are generated only for the free faces. Finally, the proposed method implemented on a set twenty-four household objects and toys, where a grasp planner based on object slicing method has been used to compute the contact-level grasp plan.

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Source: https://tomesphere.com/paper/1908.00221