3 October 1995 Ultrasonic perception of mobile robots: a comparison of competition neural network and feedforward neural network techniques for sensor array signal processing
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Abstract
For truly intelligent behavior of a mobile robot, the important ask is to make the mobile robot to understand its environment. For this reason a certain measurement device must be installed in the mobile robot. In our system we make use of a tri-aural sensor array to observe the robot environment. The tri-aural sensor array is composed of three ultrasonic sensors placed on a line. The central sensor is used as transmitter as well as receiver, the two peripheral ones are used only as receivers. By using this device, the robot can get some environment information which is represented by the reflected echoes from the objects in the sensor field. From the sampled information, the robot has to determine the number of objects as well as their positions (distance and bearing) in the sensor field. How to process these sensor array signals is our principal problem. We have developed two neural network techniques for solving this problem, one is based on a competition neural network and another based on a multi-layer feedforward neural network. In this paper, we first describe the correspondence problem in realistic circumstances and then we briefly introduce both neural network techniques. Finally we compare both methods by using simulation data.
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J. Chen, J. Chen, Jan M. Van Campenhout, Jan M. Van Campenhout, } "Ultrasonic perception of mobile robots: a comparison of competition neural network and feedforward neural network techniques for sensor array signal processing", Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); doi: 10.1117/12.222698; https://doi.org/10.1117/12.222698
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