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Nonlinear Model Predictive Control of a BMI-Guided Wheelchair for Navigation in Unknown Environments

Davide De Lazzari,Piero Simonetto,Niccolo' Turcato,Luca Tonin,Ruggero Carli

Published 2024 in European Control Conference

ABSTRACT

The ability to discern human intentions from brain signals has opened the possibility of leveraging Brain-Machine Interfaces (BMIs) for the control of robotic devices, especially benefiting individuals with severe motor disabilities. In this work, we present a novel approach for navigating a semiautonomous wheelchair towards targets generated by a BMI, all while ensuring collision avoidance. Our approach employs Nonlinear Model Predictive Control (NMPC) for real-time trajectory generation in unknown and dynamic environments. The empirical results obtained from real-world experiments clearly demonstrate the advancements of our solution over current state-of-the-art techniques. Our implementation is proven to outperform well-established methods in terms of both smoothness and alignment with the user's intended behavior.

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