An autonomous robot capable of following a predefined path using color detection — a simple yet effective system that demonstrates real-time decision-making and path correction through sensor feedback and motor control.
This project focuses on building an autonomous robot capable of following a predefined path using color detection. The idea was to design a simple yet effective system that demonstrates real-time decision-making and path correction through sensor feedback and motor control.
Goals included developing a line-following robot that detects and tracks a black path on light-colored surfaces; implementing automatic recovery behavior — performing a U-turn when the line is lost and reorienting to find the correct path; and achieving smooth, accurate movement through optimized sensor readings and motor control logic.
Designed the control system using Arduino Uno as the main controller. Integrated the TCS3200 color sensor to detect surface color contrast. Configured DC motors with an H-bridge driver for precise movement and direction control.
Programmed in Arduino IDE using C++ to process sensor input and control wheel movement. Implemented conditional logic for line detection, U-turn execution, and real-time path correction. Tuned sensor thresholds to differentiate between the black line and background surfaces.
Tested the robot on various track patterns to ensure stable navigation and smooth turning. Adjusted motor speeds and sensor placement for accurate detection during curves. Verified automatic recovery when the line was interrupted or lost.
Tuning sensor thresholds to differentiate between the black line and background surfaces reliably.
Achieving smooth turning and accurate detection during curves through motor speeds and sensor placement.
Implementing robust automatic recovery when the line is interrupted or lost (U-turn and reorientation).
Line-following robot that detects and tracks a black path on light-colored surfaces achieved.
Automatic recovery behavior with U-turn when the line is lost verified on various track patterns.
Stable navigation and smooth turning through optimized sensor readings and motor control logic.
The robot was developed through concept and circuit design, programming and control logic, and testing and optimization. Design focus: line detection, motor control, autonomous navigation logic.
Real-time decision-making and path correction through sensor feedback and motor control.
Future work could include multi-sensor fusion, speed control on straights vs curves, or obstacle detection.