Autonomous Boat Control System Design

The Autonomous Boat project demonstrates a scale model of a vessel designed for autonomous navigation and obstacle avoidance. Driven by differential steering via two DC motors controlled by a single L293D motor driver, the boat integrates sensors, fuzzy logic control, and a LabVIEW interface to ensure efficient navigation and collision prevention.

Aims and Objectives

Autonomous Navigation: Navigate in a pre-set direction while avoiding obstacles using ultrasonic sensors and fuzzy control logic.
Sensor Integration: Process input from a compass (IMU), ultrasonic sensors, and bumper switches.
Manual Override: Include a manual navigation mode for control in emergencies.
Data Visualization: Display sensor readings and control states through a LabVIEW interface.
Error Checking: Implement robust communication protocols between Arduino and LabVIEW.

Differential Steering and Motor Control

The boat is powered by two propellers, with speed differentials enabling turns. Speed and direction are controlled via LabVIEW signals sent to a master Arduino. Direction is controlled by a weight factor (Wd), ranging from -1 (hard left) to 1 (hard right). Motor speeds are dynamically adjusted based on this weight.

Sensor Array and Control Circuit

The sensor system consists of ultrasonic modules (HC-SR04) and bumper switches to detect obstacles and collisions. The circuit features two Arduino boards: one handles motor control via an L293D motor driver and process the sensors Data and another processes Compass sensor data and sent it via I2C communication protocol to the master.

Autonomous Navigation Using Fuzzy Logic

Fuzzy control rules optimize steering and speed for obstacle avoidance and path correction. States such as "Hard Left," "Easy Right," and variable speeds ("Low," "Medium," "Full") adapt to dynamic environments.

LabVIEW Interface

Visualizes sensor data and provides manual control options for navigation and system adjustments.

Communication Protocol

Data strings, with error-checking bytes, transmit between LabVIEW and Arduino, ensuring accurate command execution.

Collision Handling

On collision detection, the autonomous mode halts, defaulting to manual control until resolved.

Conclusion

This project successfully integrates autonomous navigation with robust sensor systems and a user-friendly LabVIEW interface. While relying on fuzzy logic for decision-making, the design emphasizes safety through collision detection protocols and manual override options. Differential steering ensures precise control, and the system's modular design allows for future enhancements, showcasing its applicability in real-world scenarios.

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