A New Method Investigation for Robotic Inverted Pendulum Movement and Control

The integration of sensor fusion techniques has played a crucial role in the advancement of the contemporary robot applications era. This is primarily due to the fact that numerous robot applications heavily rely on the amalgamation of data from multiple sensors, which capture information from the immediate surroundings. Examples of such applications include interactive virtual reality games, navigation systems, and fitness trackers. This study presents the implementation of a sensor fusion technique utilizing low-cost sensors, specifically a gyro sensor and a tilt sensor, to precisely estimate the balancing angle of an inverted pendulum robot system. Hence, this research study presents an innovative approach to address the issue of gyro drift, which has a detrimental impact on the precision of orientation calculations in the indirect Kalman filter-based sensor fusion. The emergence of kinematics and dynamics is observed in this particular process. The frequency responses of two distinct sensors, namely a gyro and a tilt sensor, have been subjected to analysis. A technique of sensor fusion has been utilized to counterbalance the inherent drift of the gyroscope sensor. The integration of a low-cost gyro sensor and a tilt sensor through the process of filtering facilitates the determination of the pendulum angle with efficacy, thereby eliminating the necessity of deploying more expensive sensors. The implementation of control for tracking circular trajectories has been carried out in empirical investigations. Copyright: ©2023 IIETA.