Detecting and Solving Tube Entanglement in Bin Picking Operations

• Tipo: Artigo em Revista Científica Internacional
• Data: 2020

Autores

Leao, G (Autor) Outra; Costa, CM (Autor) Outra; Armando Jorge Sousa (Autor) FEUP; Germano Veiga (Autor) FEUP

Revista

Título: Applied Sciences

Vol. 10

Página Final: 2264

Editora: MDPI

Indexação

ISI Web of Knowledge - 10 Citações

Scopus - 10 Citações

Outras Informações

ID Authenticus: P-00R-X45

DOI: 10.3390/app10072264

Abstract (EN): Featured Application The robotic bin picking solution presented in this work serves as a stepping stone towards the development of cost-effective, scalable systems for handling entangled objects. This study and its experiments focused on tube-shaped objects, which have a widespread presence in the industry. Abstract Manufacturing and production industries are increasingly turning to robots to carry out repetitive picking operations in an efficient manner. This paper focuses on tackling the novel challenge of automating the bin picking process for entangled objects, for which there is very little research. The chosen case study are sets of freely curved tubes, which are prone to occlusions and entanglement. The proposed algorithm builds a representation of the tubes as an ordered list of cylinders and joints using a point cloud acquired by a 3D scanner. This representation enables the detection of occlusions in the tubes. The solution also performs grasp planning and motion planning, by evaluating post-grasp trajectories via simulation using Gazebo and the ODE physics engine. A force/torque sensor is used to determine how many items were picked by a robot gripper and in which direction it should rotate to solve cases of entanglement. Real-life experiments with sets of PVC tubes and rubber radiator hoses showed that the robot was able to pick a single tube on the first try with success rates of 99% and 93%, respectively. This study indicates that using simulation for motion planning is a promising solution to deal with entangled objects.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 21