Fuzzy logic combined with neural algorithm to control industrial robot
Abstract
The problem of finding the optimal path for the robot arm is one of the most
important problems of industrial robot. Problem consists when robot looking for specific
routes that require the lowest power consumption. Path that established between any
two end points, can follow many paths. All these paths require different amounts of
energy depending on the distance, velocity and acceleration. Path planning for robotic
arms have a several degrees of freedom.
This problem is solved by using neuro-fuzzy techniques. Using analytical and
numerical techniques is very difficult to find a good solution. Mathematically is more
difficulty to move a robotic arm in the presence of obstacles, but child instinctively
moving his hand in the presence of obstacles. A way that allows us to progress is a
neuro-fuzzy fusion systems. Neural networks make the ability to learn, while Fuzzy
logic is based on the emulation of thinking of an expert. In addition, as hardware
technology advances, more ...and more value will be placed on solutions that can be
used in parallel processing, such as neural networks and fuzzy logic with neural
networks.
Keywords:
Robotic / Fuzzy Logic / Neural NetworkSource:
Proceedings / 11th International conference on accomplishments in Electrical and Mechanical Engineering and Information Technology, DEMI 2013, 30th May ‐ 1th June 2013, 2013, 1019-1024Publisher:
- University of Banja Luka, Faculty of Mechanical Engineering
Funding / projects:
- Sustainability and improvement of mechanical systems in energetic, material handling and conveying by using forensic engineering, environmental and robust design (RS-MESTD-Technological Development (TD or TR)-35006)
Collections
Institution/Community
Mašinski fakultetTY - CONF AU - Latinovic, Tihomir AU - Lazarević, Mihailo AU - Deaconu, Sorin AU - Sziebig, Gabor AU - Milošević, Goran PY - 2013 UR - https://machinery.mas.bg.ac.rs/handle/123456789/4587 AB - The problem of finding the optimal path for the robot arm is one of the most important problems of industrial robot. Problem consists when robot looking for specific routes that require the lowest power consumption. Path that established between any two end points, can follow many paths. All these paths require different amounts of energy depending on the distance, velocity and acceleration. Path planning for robotic arms have a several degrees of freedom. This problem is solved by using neuro-fuzzy techniques. Using analytical and numerical techniques is very difficult to find a good solution. Mathematically is more difficulty to move a robotic arm in the presence of obstacles, but child instinctively moving his hand in the presence of obstacles. A way that allows us to progress is a neuro-fuzzy fusion systems. Neural networks make the ability to learn, while Fuzzy logic is based on the emulation of thinking of an expert. In addition, as hardware technology advances, more and more value will be placed on solutions that can be used in parallel processing, such as neural networks and fuzzy logic with neural networks. PB - University of Banja Luka, Faculty of Mechanical Engineering C3 - Proceedings / 11th International conference on accomplishments in Electrical and Mechanical Engineering and Information Technology, DEMI 2013, 30th May ‐ 1th June 2013 T1 - Fuzzy logic combined with neural algorithm to control industrial robot EP - 1024 SP - 1019 UR - https://hdl.handle.net/21.15107/rcub_machinery_4587 ER -
@conference{ author = "Latinovic, Tihomir and Lazarević, Mihailo and Deaconu, Sorin and Sziebig, Gabor and Milošević, Goran", year = "2013", abstract = "The problem of finding the optimal path for the robot arm is one of the most important problems of industrial robot. Problem consists when robot looking for specific routes that require the lowest power consumption. Path that established between any two end points, can follow many paths. All these paths require different amounts of energy depending on the distance, velocity and acceleration. Path planning for robotic arms have a several degrees of freedom. This problem is solved by using neuro-fuzzy techniques. Using analytical and numerical techniques is very difficult to find a good solution. Mathematically is more difficulty to move a robotic arm in the presence of obstacles, but child instinctively moving his hand in the presence of obstacles. A way that allows us to progress is a neuro-fuzzy fusion systems. Neural networks make the ability to learn, while Fuzzy logic is based on the emulation of thinking of an expert. In addition, as hardware technology advances, more and more value will be placed on solutions that can be used in parallel processing, such as neural networks and fuzzy logic with neural networks.", publisher = "University of Banja Luka, Faculty of Mechanical Engineering", journal = "Proceedings / 11th International conference on accomplishments in Electrical and Mechanical Engineering and Information Technology, DEMI 2013, 30th May ‐ 1th June 2013", title = "Fuzzy logic combined with neural algorithm to control industrial robot", pages = "1024-1019", url = "https://hdl.handle.net/21.15107/rcub_machinery_4587" }
Latinovic, T., Lazarević, M., Deaconu, S., Sziebig, G.,& Milošević, G.. (2013). Fuzzy logic combined with neural algorithm to control industrial robot. in Proceedings / 11th International conference on accomplishments in Electrical and Mechanical Engineering and Information Technology, DEMI 2013, 30th May ‐ 1th June 2013 University of Banja Luka, Faculty of Mechanical Engineering., 1019-1024. https://hdl.handle.net/21.15107/rcub_machinery_4587
Latinovic T, Lazarević M, Deaconu S, Sziebig G, Milošević G. Fuzzy logic combined with neural algorithm to control industrial robot. in Proceedings / 11th International conference on accomplishments in Electrical and Mechanical Engineering and Information Technology, DEMI 2013, 30th May ‐ 1th June 2013. 2013;:1019-1024. https://hdl.handle.net/21.15107/rcub_machinery_4587 .
Latinovic, Tihomir, Lazarević, Mihailo, Deaconu, Sorin, Sziebig, Gabor, Milošević, Goran, "Fuzzy logic combined with neural algorithm to control industrial robot" in Proceedings / 11th International conference on accomplishments in Electrical and Mechanical Engineering and Information Technology, DEMI 2013, 30th May ‐ 1th June 2013 (2013):1019-1024, https://hdl.handle.net/21.15107/rcub_machinery_4587 .