A Kinodynamic Model for Dubins-Based Trajectory Planning in Precision Oyster Harvesting

Area of Science:

• Marine Biology
• Robotics and Automation
• Naval Architecture

Background:

• Oyster aquaculture in the U.S. suffers from inefficiencies due to a lack of precise path planning tools.
• Current dredging methods cause unnecessary seabed disturbance and inefficient shell distribution.
• Existing vessel models do not directly link steering inputs to spatial coordinates, creating a gap in maneuver planning for underactuated vessels.

Purpose of the Study:

• To address the research gap in maneuver planning for underactuated boats in oyster aquaculture.
• To develop a novel hybrid vessel kinetics model for precise path planning.
• To enable real-time, constraint-aware automation in oyster harvesting.

Main Methods:

• Developed a hybrid vessel kinetics model integrating the Nomoto model with Dubins motion primitives.
• Linked steering inputs directly to vessel motion for Cartesian coordinate path generation.
• Conducted field trials in the Chesapeake Bay to validate trajectory following performance.

Main Results:

• Achieved consistent trajectory following across varied path complexities.
• Demonstrated low average trajectory offsets: 0.01 m, 1.35 m, and 0.42 m.
• Validated the model's effectiveness in real-world aquaculture conditions.

Conclusions:

• The novel hybrid model successfully bridges the gap in maneuver planning for underactuated vessels.
• This research offers a scalable and efficient solution for automated oyster harvesting.
• The findings have significant implications for advancing sustainable aquaculture practices through automation.