Implementation of Sensor Fusion and Control Logic for Multi-Mode Operation of an Innovative Self-Balancing Microvehicle

This paper presents the development and implementation of a sensor fusion and control system for a novel selfbalancing microvehicle designed for multi-mode urban mobility. The vehicle, developed within the H2020 LEONARDO project, combines the portability of a monowheel with the intuitive handling of a kick scooter, eliminating the traditional throttle in favor of a push/pull steering column for acceleration and deceleration. To ensure stability and safety, the system employs a complementary filter to fuse accelerometer and gyroscope data, providing robust pitch angle estimation despite environmental disturbances and sensor limitations. The control architecture is based on a nonlinear inverted pendulum model, utilizing a Proportional–Derivative (PD) controller and a hierarchical state machine to manage various operational modes, including selfstabilizing trolley mode and regulated drive modes with speed limits compliant with international standards. Experimental results demonstrate the effectiveness of the sensor fusion strategy and control logic in maintaining stability, attenuating vibrations, and ensuring user safety across different urban scenarios. The proposed approach offers a significant advancement in the active stabilization of lightweight electric vehicles, addressing key challenges in micromobility safety and user experience.