Parameter Tuning of the Autonomous Boat in Fish Farming Industry with Design of Experiment

Abstract

This research studied the feasibility in applying the flight controller of the unmanned aerial vehicle on a pontoon boat in fish farming industry. A small-scale autonomous pontoon boat has been built, equipped with the open-hardware flight controller, GPS receiver, Inertial Measurement Units (IMU) and the magnetometer. A 23 factorial design based on Design of Experiment (DOE) is carried out to study the influence of three parameters (turn_rate, turn_angle and damping) on the response variable (peak-to-peak deviation from the desired trajectory). Total 24 experiments have been conducted by setting the desired trajectory as a circle with diameter 20 m. The peak-to-peak deviation in each experiment has been observed. The analyses revealed that the damping has low interaction with the turn angle and turn rate while there is a stronger interaction between the turn angle and turn rate. And the peak-to-peak deviation of the trajectory tends to decrease when the parameter damping was set to high value. The regression model has been derived and plotted as a response surface.  The optimized parameters were selected from the plot and perform the experiment with three replications. The results confirm that parameters tuning has improved the performance of the boat significantly. With the DOE approach, the impact of two or more parameters on a response, the interaction between parameters can be investigated systematically. This approach is an effective way to tuning the parameters and can be applied to various kinds of the autonomous vehicle.   A 23 factorial design based on Design of Experiment (DOE) is carried out to study the influence of three parameters (turn_rate, turn_angle and damping) on the response variable (peak-to-peak deviation from the desired trajectory). Total 24 experiments have been conducted by setting the desired trajectory as a circle with diameter 20 m. The peak-to-peak deviation in each experiment has been observed.   The analyses revealed that the damping has low interaction with the turn angle and turn rate while there is a stronger interaction between the turn angle and turn rate. And the peak-to-peak deviation of the trajectory tends to decrease when the parameter damping was set to high value. The regression model has been derived and plotted as a response surface.  The optimized parameters were selected from the plot and perform the experiment with three replications. The results confirm that parameters tuning has improved the performance of the boat significantly.   With the DOE approach, the impact of two or more parameters on a response, the interaction between parameters can be investigated systematically. This approach is an effective way to tuning the parameters and can be applied to various kinds of the autonomous vehicle