Fuzzy Logic Based Path Planning for Industrial Robot

Fuzzy Logic Based Path Planning for Industrial Robot

Supriya Sahu, Bibhuti Bhusan Choudhury
Copyright: © 2020 |Pages: 10
DOI: 10.4018/978-1-7998-1754-3.ch018
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This article describes how industrial robots are generally used to perform different tasks in industries, such as pick and place, and many more operations in industries. Among these, pick and place is a very common and frequently used task. Path planning is the most important thing in order to make any process more economical. The main focus of the research is to design a fuzzy control system for path planning for industrial robots using artificial intelligence using fuzzy logic. For the analysis, ten different tasks are tested. For fuzzy logic systems, three membership functions are analyzed and compared to find the best result. From the research, it has been found that a Gaussian membership function gives more accurate result in comparison to the other two membership functions.
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2. Methodology

The problem of finding the optimal path is the greatest problem in industries using industrial robots. The main problem arises to find the path when the cycle time is concerned. For the design of path planning, the layout of the path has major influence. The path with shortest path length and with minimum cycle time is taken as the optimal path. Therefore, it is necessary to have clear idea about all the paths in order to design for path planning. For the simulation of this particular analysis of industrial robot ten tasks has been given to the robot and robot is allowed to move from any starting task, passing through all the task and end with the last task. The task arrangement is shown in the Figure 1 and is specified by numbers from 1 to 10. In industries industrial robots are used for many operations such as drilling holes using the drilling tools by replacing the griper. To increases the performance of robot it has to travel each and every object by performing the required operation and move to the next and complete the task with minimum time period.

Figure 1.

Arrangement of task


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