Real-Time Trajectory Tracking of a Piezoelectric Microrobot Using Asynchronous Fusion of Vision Cameras and Laser Sensors

This study developed a multisensor asynchronous fusion method for vision cameras and laser sensors for real-time tracking of a millimeter-scale piezoelectric microrobot with high sampling rates. The design, manufacture, and realization of the proposed microrobot using a monolithic integrated manufacturing process is realized with a size of $36 \times 36 \times 18$ mm and a weight of 4.9 g. Two local estimators for the vision camera and laser sensors are established independently for 2-D tracking of the millimeter-scale microrobot. An asynchronous fusion method for the camera and laser sensors is developed by optimally weighting the two local estimators in a linear minimum variance framework using the Lagrange multiplier method at the synchronized update time. High-precision 2-D trajectory tracking of the proposed microrobot was achieved with an average velocity of 301.6 mm/s and a sampling rate of up to 4000 Hz. Experiments tracking different trajectories of the microrobot at different velocities and sampling rates demonstrated the effectiveness of the proposed fusion method. Note to Practitioners—This paper aims to enhance the real-time trajectory tracking accuracy of microrobots. The parallel microrobot is fabricated by a monolithic integrated manufacturing process, and has a small dimension of $36 \times 36 \times 18$ mm. An asynchronous fusion method of the camera and laser sensors is proposed by optimally weighting in a linear minimum variance framework using the LaGrange multiplier method at the synchronized update time. Furthermore, high-precision 2-D trajectory tracking of the proposed microrobot is realized with an average velocity of 301.6 mm/s and a sampling rate of up to 4000 Hz. Experiments demonstrate the effectiveness of the proposed fusion method. It is of great importance to researchers and engineers in trajectory tracking and positioning control of microrobots with high precision and sampling rates.