A collection of Arduino and Processing projects developed for COGS 300 (Designing and Understanding Cognitive Systems) at UBC. Covers progressive robotics topics from basic motor control through Bayesian object tracking and autonomous maze navigation.

PWM-based dual motor control with multiple command interfaces: serial console, WiFi/UDP remote control, and a Processing GUI with D-pad and speed slider.

Encoder-based odometry with interrupt-driven pulse counting, BLE wireless control via GATT protocol, and photoresistor-based line detection.

Autonomous left-wall-following using dual ultrasonic sensors. Implements a state machine with proportional steering and drift correction to maintain constant wall distance.

Reactive line-following using dual IR reflectance sensors with binary thresholding. Includes drift-corrected variant with tuned timing for smoother trajectories.

Servo-mounted rotating ultrasonic sensor creates a 180-degree depth map. A Bayesian filter calculates object probability across scan angles using variance-based likelihood estimation and belief diffusion. Proportional steering drives the robot toward the highest-probability target.

Bayesian filter details:

• Prior: P(object) = 0.5 uniform across all angles
• Likelihood: Variance threshold (30 cm) detects depth discontinuities -- high variance yields L(object) = 0.85
• Update: Standard Bayes rule with normalization
• Diffusion: 5% belief spreading to neighboring angles to account for object motion

Maze solving using the right-hand wall-following heuristic with dual ultrasonic sensors and empirical motor asymmetry compensation.

• Bayesian inference -- Probabilistic object detection with likelihood models and belief propagation
• Proportional control -- Continuous steering based on sensor error for wall following and object tracking
• Interrupt service routines -- Hardware interrupts for accurate encoder pulse counting
• State machines -- Multi-state FSMs for autonomous navigation behaviors
• BLE GATT protocol -- Custom service and characteristic UUIDs for wireless robot control
• Sensor fusion -- Combining ultrasonic, IR, encoder, and photoresistor data for decision-making

COGS300-6/
├── src/MyRobot-V1/          # Base template (motor control + serial logging)
├── Lab 03/                  # Motor control, WiFi/UDP, Processing GUI
├── Lab 04/                  # Encoders, BLE, photoresistor, CSV logging
├── Lab 05/                  # Wall following with ultrasonic sensors
├── Lab 06/                  # Line following with IR sensors
├── Lab 07/                  # Bayesian object tracking with servo scanning
├── Lab 08/                  # Maze navigation
└── docs/                    # Getting started reference

• Arduino IDE (v2.x recommended)
• Processing (for GUI sketches)
• Arduino board (Uno for most labs, Nano 33 BLE for Lab 04)

1. Clone the repository:

   git clone https://github.com/MelodyccLo/COGS300-6.git

2. Open any .ino file in the Arduino IDE.
3. Select your board and port under Tools.
4. Click Upload.
5. For Processing sketches (.pde), open in Processing IDE and click Run.

Built for COGS 300 at the University of British Columbia.