Robotic bin-picking system based on a revolving vision system

Pochyly, Ales; Kubela, Tomas; Singule, Vladislav; Cihak, Petr

doi:10.1109/edpe.2017.8123228

Cited by 8 publications

(4 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, suction grippers are usually more compact and can reach the edges of the bin more easily than parallel grippers. In [22], an eccentrically mounted gripper and chamfered bin edges have been exploited in order to decrease the rate of this type of failure; • Grasping failures: even though object recognition and pose estimation are successful, grasping can still fail for a number of reasons such as a porous or uneven surface, insufficient friction, grasp interference, entangled objects or multiple grasping of neighboring objects. A very detailed investigation of grasping failures in bin-picking applications with different end effectors can be found in [20].…”

Section: Bin-picking Failuresmentioning

confidence: 99%

Improving Robotic Bin-Picking Performances through Human–Robot Collaboration

2023

View full text Add to dashboard Cite

The automation of bin-picking processes has been a research topic for almost two decades. General-purpose equipment, however, still does not show adequate success rates to find application in most industrial tasks. Human–robot collaboration in bin–picking tasks can increase the success rate by exploiting human perception and handling skills and the robot ability to perform repetitive tasks. The aim of this paper, starting from a general-purpose industrial bin picking equipment comprising a 3D–structured light vision system and a collaborative robot, consists in enhancing its performance and possible applications through human–robot collaboration. To achieve successful and fluent human–robot collaboration, the robotic workcell must meet some hardware and software requirements that are defined below. The proposed strategy is tested in some sample tests: the results of the experimental tests show that collaborative functions can be particularly useful to overcome typical bin picking failures and to improve the fault tolerance of the system, increasing its flexibility and reducing downtimes.

show abstract

Section: Bin-picking Failuresmentioning

confidence: 99%

Improving Robotic Bin-Picking Performances through Human–Robot Collaboration

2023

View full text Add to dashboard Cite

show abstract

“…Thus, enhancing the quality of the data acquired and processed by a vision system is important. Different types of machine vision systems have been integrated with robotic arms for different bin-picking scenarios [8][9][10][11][12][13][14][15]. The choice of a particular system determines how the acquired data needs to be addressed by the post-processing algorithms.…”

Section: Introductionmentioning

confidence: 99%

Filtering Organized 3D Point Clouds for Bin Picking Applications

Franaszek,

Rachakonda,

Saidi

2024

Applied Sciences

View full text Add to dashboard Cite

In robotic bin-picking applications, autonomous robot action is guided by a perception system integrated with the robot. Unfortunately, many perception systems output data contaminated by spurious points that have no correspondence to the real physical objects. Such spurious points in 3D data are the outliers that may spoil obstacle avoidance planning executed by the robot controller and impede the segmentation of individual parts in the bin. Thus, they need to be removed. Many outlier removal procedures have been proposed that work very well on unorganized 3D point clouds acquired for different, mostly outdoor, scenarios, but these usually do not transfer well to the manufacturing domain. This paper presents a new filtering technique specifically designed to deal with the organized 3D point cloud acquired from a cluttered scene, which is typical for a bin-picking task. The new procedure was tested on six different datasets (bins filled with different parts) and its performance was compared with the generic statistical outlier removal procedure. The new method outperforms the general procedure in terms of filtering efficacy, especially on datasets heavily contaminated by numerous outliers.

show abstract

“…Therefore, this paper takes the stamping press in the metal cold forging process [9] as the scene and considers the problems of manufacturing and production to establish a system with the characteristics of both CPMS and CPPS. In addition, stamping press equipment is mainly used to manufacture products similar to wheel suspension [10], and the three devices covered by the overall process can be serially connected and communicated through the computing framework of the robot [11] to improve the overall manufacturing efficiency. Based on the whole automation architecture made of metal in this paper we propose its approach to solving the problem, the main contributions of which are as follows:…”

Section: Introductionmentioning

confidence: 99%

Integrating a Fast and Reliable Robotic Hooking System for Enhanced Stamping Press Processes in Smart Manufacturing

Chen,

Lai

2023

Preprint

View full text Add to dashboard Cite

Facing the diversity of the market, the industry has to move towards Industry 4.0, and smart manufacturing based on cyber-physical systems is the only way to move towards Industry 4.0. However, there are two key concepts in Industry 4.0: cyber-physical systems (CPS) and digital twins (DT). In the paper, we propose a smart manufacturing system suitable for Stamping Press Processes based on the CPS concept and use DT to establish a manufacturing-end robot guidance generation model. In the smart manufacturing system of Stamping Press Processes, fog nodes are used to connect three major architectures including device health diagnosis, manufacturing device and material traceability. In addition, a special hook end point is designed, and its lightweight visual guidance generation model is established to improve the production efficiency of the manufacturing end in product manufacturing.

show abstract

Robotic bin-picking system based on a revolving vision system

Cited by 8 publications

References 11 publications

Improving Robotic Bin-Picking Performances through Human–Robot Collaboration

Improving Robotic Bin-Picking Performances through Human–Robot Collaboration

Filtering Organized 3D Point Clouds for Bin Picking Applications

Integrating a Fast and Reliable Robotic Hooking System for Enhanced Stamping Press Processes in Smart Manufacturing

Contact Info

Product

Resources

About