The Dextron Competition challenges participants to design the fastest robot capable of autonomously navigating a complex predefined track while maintaining alignment with designated paths. Our team aims to create a robot that uses integrated circuits (ICs) instead of Arduino plug-in modules for greater control and efficiency.
- Arduino Nano V3.0: Manages all robotic actions.
- L293D Push-Pull Four-Channel Motor Driver: Controls motor speed and direction.
- Micro Motor N30 (3.7V, 0.3A, approx. 32,800 RPM) x 2: Provides motion.
- IR Speed Sensor Module with Encoder x 2: Measures speed and direction.
- TCRT5000 Reflective Optical Infrared IR Sensor x 7: Detects surface details and line positions.
- 30-pin Single Row Female Headers
- 16-pin Normal IC Base (2.54mm) x 2
- LM324N General Purpose Amplifier x 2
- 14-pin Normal IC Base (2.54mm) x 2
- 10k Variable Resistors x 1
- 150 Ohm 1W Resistors x 7
- 10k 1W Resistors x 7
- KF128V 5.08mm Pitch 2-Pin 2-Way Screw Terminal Block PCB Mount x 2
- Tyre Wheel D:35mm x 2
- 3.7V 2800mAh 18650 Li-ion Rechargeable Battery x 2
- Battery Holder Case for 2x18650
- Programming Language: C++
- Development Environment: Arduino IDE
The robot must adhere to the following constraints:
- Size: Maximum dimensions of 20cm x 20cm
- Power: Maximum voltage of 24V
- Line Thickness: 3 cm
- Path Complexity:
- Two types of backgrounds: black lines on a white background and white lines on a black background.
- Acute angle lines with a minimum 45-degree angle.
- Junctions (T and L), Cross Lines.
- Turns (L and U) and bends.
- Dotted lines, circles, and cross circles.
- Bridges (max. height 2.5cm, width 30cm) and narrow ramps (max. height 2.5cm, width 10cm).
- Time Limit: Maximum time of 10 minutes to complete the course, including calibration time. The robot can only use the starting square for calibration.
The robot's algorithm is designed to address specific tasks effectively:
- Auto Calibration: The robot calibrates itself inside the starting box, assuming it is a single color (either white or black). It performs small oscillations to read surface colors and establishes a range for the specific surface type.
- Dynamic Color Detection: While operating, the robot collects additional readings to define the color range of the line to be followed. It prioritizes background readings over line readings to enhance line-following accuracy.
- Crossing Circular Areas: The robot employs a chord-based approach to navigate circular areas efficiently.
- Speed Measurement and Control: It measures wheel speed to maintain precise speed limits during navigation.
- Acute Angle Handling: The algorithm identifies acute angle turns and adjusts the robot's speed accordingly to navigate these turns smoothly.
The team members: