scholarly journals AI based combined scheduling and motion planning in flexible robotic assembly lines

Procedia CIRP ◽  
2019 ◽  
Vol 86 ◽  
pp. 74-79 ◽  
Author(s):  
Niki Kousi ◽  
Dimosthenis Dimosthenopoulos ◽  
Aleksandros-Stereos Matthaiakis ◽  
George Michalos ◽  
Sotiris Makris
Author(s):  
Yi Liu ◽  
Ming Cong ◽  
Hang Dong ◽  
Dong Liu

Purpose The purpose of this paper is to propose a new method based on three-dimensional (3D) vision technologies and human skill integrated deep learning to solve assembly positioning task such as peg-in-hole. Design/methodology/approach Hybrid camera configuration was used to provide the global and local views. Eye-in-hand mode guided the peg to be in contact with the hole plate using 3D vision in global view. When the peg was in contact with the workpiece surface, eye-to-hand mode provided the local view to accomplish peg-hole positioning based on trained CNN. Findings The results of assembly positioning experiments proved that the proposed method successfully distinguished the target hole from the other same size holes according to the CNN. The robot planned the motion according to the depth images and human skill guide line. The final positioning precision was good enough for the robot to carry out force controlled assembly. Practical implications The developed framework can have an important impact on robotic assembly positioning process, which combine with the existing force-guidance assembly technology as to build a whole set of autonomous assembly technology. Originality/value This paper proposed a new approach to the robotic assembly positioning based on 3D visual technologies and human skill integrated deep learning. Dual cameras swapping mode was used to provide visual feedback for the entire assembly motion planning process. The proposed workpiece positioning method provided an effective disturbance rejection, autonomous motion planning and increased overall performance with depth images feedback. The proposed peg-hole positioning method with human skill integrated provided the capability of target perceptual aliasing avoiding and successive motion decision for the robotic assembly manipulation.


2019 ◽  
Vol 65 ◽  
pp. 256-270 ◽  
Author(s):  
Mukund Nilakantan Janardhanan ◽  
Zixiang Li ◽  
Grzegorz Bocewicz ◽  
Zbigniew Banaszak ◽  
Peter Nielsen

2019 ◽  
Vol 36 (6) ◽  
pp. 1868-1892 ◽  
Author(s):  
Binghai Zhou ◽  
Qiong Wu

Purpose The extensive applications of the industrial robots have made the optimization of assembly lines more complicated. The purpose of this paper is to develop a balancing method of both workstation time and station area to improve the efficiency and productivity of the robotic assembly lines. A tradeoff was made between two conflicting objective functions, minimizing the number of workstations and minimizing the area of each workstation. Design/methodology/approach This research proposes an optimal method for balancing robotic assembly lines with space consideration and reducing robot changeover and area for tools and fixtures to further minimize assembly line area and cycle time. Due to the NP-hard nature of the considered problem, an improved multi-objective immune clonal selection algorithm is proposed to solve this constrained multi-objective optimization problem, and a special coding scheme is designed for the problem. To enhance the performance of the algorithm, several strategies including elite strategy and global search are introduced. Findings A set of instances of different problem scales are optimized and the results are compared with two other high-performing multi-objective algorithms to evaluate the efficiency and superiority of the proposed algorithm. It is found that the proposed method can efficiently solve the real-world size case of time and space robotic assembly line balancing problems. Originality/value For the first time in the robotic assembly line balancing problems, an assignment-based tool area and a sequence-based changeover time are took into consideration. Furthermore, a mathematical model with bi-objective functions of minimizing the number of workstations and area of each station was developed. To solve the proposed problem, an improved multi-objective immune clonal selection algorithm was proposed and a special coding scheme is designed.


Procedia CIRP ◽  
2019 ◽  
Vol 81 ◽  
pp. 1429-1434 ◽  
Author(s):  
Niki Kousi ◽  
Christos Stoubos ◽  
Christos Gkournelos ◽  
George Michalos ◽  
Sotiris Makris

2019 ◽  
Vol 28 ◽  
pp. 121-126 ◽  
Author(s):  
Niki Kousi ◽  
Christos Gkournelos ◽  
Sotiris Aivaliotis ◽  
Christos Giannoulis ◽  
George Michalos ◽  
...  

2001 ◽  
Author(s):  
Byunghoon Chung ◽  
Sooyong Lee

Abstract Force guided assembly is a control scheme to guide a workpiece based on a stored map from forces to a correction of motion. Based on the geometry of the workpiece and its kinematic behavior in interacting with the environment, the functional map relating the correction of motion to force measurements is generated and stored as a control law. Central to the design of force guided control is how to synthesize this functional map. Although these explicit force-guided controls are a useful concept, particularly for the monitoring of assembly processes, there are inherent difficulties in applying it to real world problems. In real assembly lines, pipe insertion task, for instance, has been performed only by human workers. Skilled workers insert pipes by perturbing the pipes in order to avoid jamming as well as to determine which way to correct the motion. According to them, the skilled workers monitor obstructing forces in response to the applied perturbation, and modify their motion accordingly. The proposed perturbation/correlation method was motivated by this human perception and action : perturbing the pipe, observing the reaction to the perturbation and correcting the trajectory. In this paper, we propose a novel technique for acquiring effective force information despite sensor noise and friction. Instead of simply receiving force signals from the process, we give perturbation to the robot and measure the reaction forces to the perturbation. By taking the correlation between the perturbation signal and the reaction forces, reliable and useful information for guiding the robot would be extracted. It is expected that this perturbed force measurement provides much richer force information than that of stationary measurement. The perturbation/Correlation method presented in this paper is not only effective for reducing friction, but also effective for obtaining useful information for guiding the robot towards a desired direction. Preliminary experimental results with one directional perturbation are shown in this paper. Extensive mathematical analysis shows the potential application to assemblies in higher dimension.


2012 ◽  
Vol 45 (6) ◽  
pp. 1353-1358 ◽  
Author(s):  
Slim Daoud ◽  
Lionel Amodeo ◽  
Farouk Yalaoui ◽  
Hicham Chehade ◽  
Philippe Duperray

Sign in / Sign up

Export Citation Format

Share Document