Myon is a humanoid robot where each joint is controlled independently by a supervised bio-inspired artificial neural network inducing the correction of a number of distinct actions depending on the excitation. One of the control strategies, which the network, located within a certain joint, may implement, allows a controlled motion of the limb connected to the joint from a stable state up to a prescribed height and the maintenance of the new position afterwards. The original approach adopted for this control operation is stable and robust but results in slow and energy-inefficient limb movements. This work proposes a novel, low-power, timeefficient and adaptive memristor-centred control strategy for the aforementioned robot action. The idea is based upon the exploitation of the combined ability of memristors to store and process data in the same physical location. The part I paper sets the theoretic foundations for the memcomputing paradigm to robot motion control, while the part II manuscript shall demonstrate its benefits over the original approach in terms of energy, and speed, and the inheritance from the standard strategy of a good level of adaptability to changes in the limb load on the basis of the analysis of circuit-theoretic models adopting an ideal and a real memristor, respectively.

Memristor-enhanced humanoid robot control system: Part I - theory behind the novel memcomputing paradigm / Ascoli, A; Baumann, D; Tetzlaff, R; Chua, Lo; Hild, M. - In: INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS. - ISSN 0098-9886. - ELETTRONICO. - 46:(2018), pp. 155-183. [10.1002/cta.2431]

Memristor-enhanced humanoid robot control system: Part I - theory behind the novel memcomputing paradigm

Ascoli A;
2018

Abstract

Myon is a humanoid robot where each joint is controlled independently by a supervised bio-inspired artificial neural network inducing the correction of a number of distinct actions depending on the excitation. One of the control strategies, which the network, located within a certain joint, may implement, allows a controlled motion of the limb connected to the joint from a stable state up to a prescribed height and the maintenance of the new position afterwards. The original approach adopted for this control operation is stable and robust but results in slow and energy-inefficient limb movements. This work proposes a novel, low-power, timeefficient and adaptive memristor-centred control strategy for the aforementioned robot action. The idea is based upon the exploitation of the combined ability of memristors to store and process data in the same physical location. The part I paper sets the theoretic foundations for the memcomputing paradigm to robot motion control, while the part II manuscript shall demonstrate its benefits over the original approach in terms of energy, and speed, and the inheritance from the standard strategy of a good level of adaptability to changes in the limb load on the basis of the analysis of circuit-theoretic models adopting an ideal and a real memristor, respectively.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2989730