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Insect-Inspired Body Size Learning Model on a Humanoid Robot

Paolo Arena, Luca Patané, Dario Sanalitro, Alessandra Vitanza

Year
2018
Citations
3

Abstract

In this paper an insect-inspired body size learning algorithm is adopted in a humanoid robot and a control system, mainly developed with spiking neurons, is proposed. It implements an evaluation of distances by using the typical parallax method performed by different insect species, such as Drosophila melanogaster. A Darwin-OP robot was used as testbed to demonstrate the potential application of the learning method on a humanoid structure. The robot, equipped with a hand extension, was free to move in an environment to discover objects. As consequence, it was able to learn, using an operant conditioning, which objects can be reached, via the estimation of their distance on varying the length of the equipped tool. The learning scheme was tested both in a dynamical simulation environment and with the Darwin-OP robot.

Keywords

Humanoid robotTestbedComputer scienceRobotArtificial intelligenceDarwin (ADL)ParallaxRobot learningScheme (mathematics)Computer vision

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