Control of real-world complex robots using a biologically inspired algorithm

Authors:
Fabio Dallalibera;Shuhei Ikemoto;Hiroshi Ishiguro;Koh Hosoda
Affiliations:
Osaka University, JSPS, Toyonaka, Japan 560-8531;Department of Multimedia Engineering, Graduate School of Information Science and Technology, Suita, Japan 565-0871;Department of Systems Innovation, Graduate School of Engineering Science, Osaka University, Toyonaka, Japan 560-8531;Department of Multimedia Engineering, Graduate School of Information Science and Technology, Suita, Japan 565-0871
Venue:
Artificial Life and Robotics
Year:
2012

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A parameterless biologically inspired control algorithm robust to nonlinearities, dead-times and low-pass filtering effects

SIMPAR'10 Proceedings of the Second international conference on Simulation, modeling, and programming for autonomous robots

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Abstract

Elementary living beings, like bacteria, are able to reach food sources using only limited and very noisy sensory information. In this paper, we describe a very simple algorithm inspired from bacteria chemotaxis. We present a Markov chain model for studying the effect of noise on the behavior of an agent that moves according to this algorithm, and we show that, counterintuitively, the application of noise can increase the expected average performance over a fixed available time. After this theoretical analysis, experiments on real-world application of this algorithm are introduced. In particular, we show that the algorithm is able to control a complex robot arm, actuated by 17 McKibben pneumatic artificial muscles, without the need of any model of the robot or of its environment.