Design and Simulation of a Vision-Based Automatic Trout Fish-Processing Robot

Abstract

Today, industrial automation is being applied in a wide range of fields. The initial modeling of robots and mechanical systems together with simulation results in optimal systems. In this study, the designed system is simulated to obtain the required velocities, accelerations and torques of the actuating arms in a vision-based automatic system. Due to the slippery skin of fish and the low friction coefficient, it is not easy to design an optimal tool to handle fish. Since the fish-processing operation is undertaken step by step and provides fish stability, it is essential that the gripper enables different processing operations along the system. The proposed system performs belly-cutting, beheading, gutting, and cleaning stages for different fish sizes, based on the extracted dimensions of the vision system. In the head-cutting section, the average speed of the actuator jack was considered as 500 mm s−1. Under these conditions, the maximum required force to provide this speed was 332.45 N. In the belly-cutting subsystem, the required torque for the stepper motor resulted in 1.79–2.15 N m. Finally, the maximum required torque for the gutting stepper motor was calculated as 0.69 N m in the tested processing capacities.