A decision support system for robotic motion planning using artificial neural networks

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Title:	A decision support system for robotic motion planning using artificial neural networks
Author:	Ma, Heng
Description:	The introduction of flexible manufacturing systems (FMS) has increased the importance of industrial robotic manipulators. Traditional robotic controllers have encountered limited success due to their lack of flexibility in real time. Artificial neural networks with their capability to learn and adapt to ever changing environments have been recently introduced to the area of real-time robotic control. In this research, two steps of artificial neural network systems were employed for planning robot motions with a four-degree-of-freedom robotic manipulator. The two-step procedure determined the accessibility of a target point and the optimal robot configuration to reach that point. The employment of artificial neural networks showed increased adaptability and efficiency in robotic manipulation in comparison with traditional robotic controllers. The accuracy and training time of the artificial neural network systems present groundwork for ongoing research.
Permanent Link:	http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1172859329 http://hdl.handle.net/2374.OX/14834
Date:	1992

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