Gait Parameter Tuning Using Bayesian Optimisation for an Alligator-Inspired Amphibious Robot
Abstract
This paper reports a sample-efficient Bayesian optimization approach for tuning the locomotion parameters of an in-house developed twelve degrees of freedom alligator-inspired amphibious robot. An optimization framework is used wherein the objective is to maximize the mean robot speed obtained via physical experiments performed on terrains with varying friction and inclinations and in the aquatic environment for swimming locomotion. We obtained an improvement in the mean robot speed by a factor of up to 6.38 using the developed approach over randomly generated locomotion parameters in 15 iterations.
Simulation model of Alli-bot developed in CoppeliaSim 50 .
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Calculation of error angle in the laboratory frame-of-reference.
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Experimental setup.
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Conflict of interest
“Authors state no conflict of interest”
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This research received no external funding or grants
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