Abstract
This paper addresses fuzzy-logic-based reinforcement learning architecture and experimental results for the interaction between an artificial robot and a living bio-insect. The main goal of this research is to drag the bio-insect towards the desired goal area without any human aid. To achieve the goal, we seek to design robot intelligence architecture such that the robot can drag the bio-insect using its own learning mechanism. The main difficulties of this research are to find an interaction mechanism between the robot and bio-insect and to design a robot intelligence architecture. In simple interaction experiment, the bio-insect does not react to stimuli such as light, vibration, or artificial robot motion. From various trials-and-error efforts, we empirically found an actuation mechanism for the interaction between the robot and bio-insect. Nevertheless, it is difficult to control the movement of the bio-insect due to its uncertain and complex behavior. For the artificial robot, we design a fuzzy-logic-based reinforcement learning architecture that helps the artificial robot learn how to control the movement of the bio-insect under uncertain and complex behavior. Here, we present the experimental results regarding the interaction between an artificial robot and a bio-insect.
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Reference from: http://www.conceptlab.com/roachbot/.
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Acknowledgments
This research was supported by the National Research Foundation of Korea (NRF) (No. NRF-2011-0021474).
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Communicated by A. Lotfi.
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Son, JH., Ahn, HS. Bio-insect and artificial robot interaction: learning mechanism and experiment. Soft Comput 18, 1127–1141 (2014). https://doi.org/10.1007/s00500-013-1133-4
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DOI: https://doi.org/10.1007/s00500-013-1133-4