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A Novel Adaptive Controller for Robot Manipulators Based on Active Inference | IEEE Journals & Magazine | IEEE Xplore
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A Novel Adaptive Controller for Robot Manipulators Based on Active Inference


Abstract:

More adaptive controllers for robot manipulators are needed, which can deal with large model uncertainties. This letter presents a novel active inference controller (AIC)...Show More

Abstract:

More adaptive controllers for robot manipulators are needed, which can deal with large model uncertainties. This letter presents a novel active inference controller (AIC) as an adaptive control scheme for industrial robots. This scheme is easily scalable to high degrees-of-freedom, and it maintains high performance even in the presence of large unmodeled dynamics. The proposed method is based on active inference, a promising neuroscientific theory of the brain, which describes a biologically plausible algorithm for perception and action. In this work, we formulate active inference from a control perspective, deriving a model-free control law which is less sensitive to unmodeled dynamics. The performance and the adaptive properties of the algorithm are compared to a state-of-the-art model reference adaptive controller (MRAC) in an experimental setup with a real 7-DOF robot arm. The results showed that the AIC outperformed the MRAC in terms of adaptability, providing a more general control law. This confirmed the relevance of active inference for robot control.
Published in: IEEE Robotics and Automation Letters ( Volume: 5, Issue: 2, April 2020)
Page(s): 2973 - 2980
Date of Publication: 17 February 2020

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