Cooperative motion planning of dual industrial robots via offline programming

2018 ◽  
Author(s):  
Ju Haihua ◽  
Wu Dongyu ◽  
Hu Fuwen
Keyword(s):  
Motion Planning ◽  
Industrial Robots ◽  
Offline Programming ◽  
Cooperative Motion

scholarly journals A Two Layered Optimal Approach towards Cooperative Motion Planning of Unmanned Surface Vehicles in a Constrained Maritime Environment

2018 ◽  
Vol 51 (29) ◽  
pp. 378-383 ◽  
Author(s):  
Marco Bibuli ◽  
Yogang Singh ◽  
Sanjay Sharma ◽  
Robert Sutton ◽  
Daniel Hatton ◽  
...  
Keyword(s):  
Motion Planning ◽  
Unmanned Surface Vehicles ◽  
Cooperative Motion ◽  
Optimal Approach ◽  
Maritime Environment

scholarly journals Maximizing the Coverage of Roadmap Graph for Optimal Motion Planning

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Jae-Han Park ◽  
Tae-Woong Yoon
Keyword(s):  
Motion Planning ◽  
Industry 4.0 ◽  
Industrial Robot ◽  
Efficient Solutions ◽  
Industrial Robots ◽  
Optimal Motion ◽  
Optimal Motion Planning ◽  
Planning Problems ◽  
Complex Planning ◽  
Satisfactory Quality

Automated motion-planning technologies for industrial robots are critical for their application to Industry 4.0. Various sampling-based methods have been studied to generate the collision-free motion of articulated industrial robots. Such sampling-based methods provide efficient solutions to complex planning problems, but their limitations hinder the attainment of optimal results. This paper considers a method to obtain the optimal results in the roadmap algorithm that is representative of the sampling-based method. We define the coverage of a graph as a performance index of its optimality as constructed by a sampling-based algorithm and propose an optimization algorithm that can maximize graph coverage in the configuration space. The proposed method was applied to the model of an industrial robot, and the results of the simulation confirm that the roadmap graph obtained by the proposed algorithm can generate results of satisfactory quality in path-finding tests under various conditions.

Path Planning with Motion Optimization for Car Body-in-White Industrial Robot Applications

2012 ◽  
Vol 605-607 ◽  
pp. 1595-1599 ◽  
Author(s):  
Pavol Božek ◽  
Kamil Trnka
Keyword(s):  
Motion Planning ◽  
Industrial Robot ◽  
Welding Process ◽  
Current Method ◽  
Industrial Robots ◽  
Motion Optimization ◽  
Body In White ◽  
Time And Energy ◽  
Simulation Systems ◽  
Robot Path

This paper discusses the problem of effective motion planning for industrial robots. The first part dealt with current method for off-line motion planning. In the second part the presented work is done by one of the simulation systems with automatic trajectory generation and off-line programming capability. A spot welding process is involved. The practical application of this step strongly depends on the method for robot path optimization with high accuracy, thus transform the path into a time and energy optimal robot program for the real world, which is discussed in the third step.

scholarly journals Motion Planning for Industrial Robots using Reinforcement Learning

Procedia CIRP ◽  
2017 ◽  
Vol 63 ◽  
pp. 107-112 ◽  
Author(s):  
Richard Meyes ◽  
Hasan Tercan ◽  
Simon Roggendorf ◽  
Thomas Thiele ◽  
Christian Büscher ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Motion Planning ◽  
Industrial Robots

scholarly journals Development of a Robot System for Advanced High Quality Manufacturing Processes

10.14311/792 ◽  
2006 ◽  
Vol 46 (1) ◽  
Author(s):  
B. Kuhlenkoetter
Keyword(s):  
Error Compensation ◽  
Industrial Robots ◽  
Manufacturing Processes ◽  
Robot System ◽  
Offline Programming ◽  
Learning Skill ◽  
Human Labour ◽  
Robot Technology ◽  
Set Up ◽  
Standard Operations

Grinding and polishing are standard operations in material processing which are nowadays automated with the help of industrial robots in order to relieve human labour and optimize the profitability of production. However, it is expensive to adapt present systems to the production of other part geometries and operation cycles, and therefore adaptations are economically applicable only for large batch sizes.This project develops an “intelligent” robot system that obtains sensory skills due to the linkage of innovative robot technology and image processing systems via new software. With this system even the smallest error on highly-polished, mirror-like surfaces can be detected objectively and reproducibly. In addition, the system will be capable of establishing an optimum error compensation strategy dependent on the error data, as well as generating and realizing operating programmes. For this purpose it is given a manual-learning skill. A new offline-programming and simulating system for exacting operation processes makes it easier to set up, change and optimize robot programmes, thus making it useful for the operator. 

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