Fast geometry-based computation of grasping points on three-dimensional point clouds

36Citations
Citations of this article
51Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Industrial and service robots deal with the complex task of grasping objects that have different shapes and which are seen from diverse points of view. In order to autonomously perform grasps, the robot must calculate where to place its robotic hand to ensure that the grasp is stable. We propose a method to find the best pair of grasping points given a three-dimensional point cloud with the partial view of an unknown object. We use a set of straightforward geometric rules to explore the cloud and propose grasping points on the surface of the object. We then adapt the pair of contacts to a multi-fingered hand used in experimentation. We prove that, after performing 500 grasps of different objects, our approach is fast, taking an average of 17.5 ms to propose contacts, while attaining a grasp success rate of 85.5%. Moreover, the method is sufficiently flexible and stable to work with objects in changing environments, such as those confronted by industrial or service robots.

Cite

CITATION STYLE

APA

Zapata-Impata, B. S., Gil, P., Pomares, J., & Torres, F. (2019). Fast geometry-based computation of grasping points on three-dimensional point clouds. International Journal of Advanced Robotic Systems, 16(1). https://doi.org/10.1177/1729881419831846

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free