Session 2

Programming & Algorithm Implementation

The second session of Tracktion focuses on advanced programming techniques and algorithm optimization for autonomous line-following robots. Building upon the hardware foundation from Session 1, participants dive deep into software development and real-time control systems.

Learning Objectives

Participants will master PID control algorithms, implement sensor calibration techniques, and develop robust decision-making logic for their robots. The session emphasizes algorithm optimization, performance tuning, and real-world testing scenarios to ensure reliable autonomous navigation.

PID Control Algorithms

The session begins with an in-depth exploration of Proportional-Integral-Derivative (PID) control systems. Participants learn how to implement smooth movement algorithms that enable their robots to follow lines with precision. Hands-on coding exercises demonstrate the impact of different PID parameters on robot behavior.

Sensor Calibration & Noise Filtering

Advanced sensor management techniques are covered, including calibration procedures for different lighting conditions and surface types. Participants implement noise filtering algorithms to improve sensor reliability and learn about adaptive threshold systems that enhance robot performance in varying environments.

Real-time Decision Making

The core of autonomous navigation lies in real-time decision making. Participants develop algorithms for path correction, obstacle detection, and junction handling. Special attention is given to optimizing response times and ensuring smooth transitions between different movement states.

Performance Optimization & Testing

The session concludes with comprehensive testing on practice tracks. Participants fine-tune their algorithms, debug issues, and optimize performance for speed and accuracy. Multiple testing scenarios prepare them for various real-world challenges their robots might encounter.

Algorithm Integration

Participants learn to integrate all components into a cohesive system, combining sensor input processing, decision-making logic, and motor control into a seamless autonomous navigation system. The session emphasizes code structure, debugging techniques, and systematic testing approaches.