International Journal of Robotics and Autonomous Systems ISSN: 3107-7382 (Online)

Authors: Dr. Sneha Kulkarni, Ankit Rao

Abstract: Color detection in robotics represents a significant leap in the field of autonomous and semi-autonomous systems, enabling real-time decision-making based on visual data. This paper explores the integration of camera modules, specifically the Pi Camera and OpenCV library, into robotic platforms to identify and respond to colored objects. The ability to detect colors allows robots to interact more intuitively with their environment, opening avenues in automation, sorting, rescue operations, and object tracking. The methodology involves capturing live video feeds, converting frames to HSV color space for efficient segmentation, and defining specific thresholds to isolate target colors. The processed image data is then analyzed by onboard microcontrollers or single-board computers like the Raspberry Pi, triggering robotic actions based on identified hues. Various real-world implementations such as color-based sorting in industrial robotics, traffic signal recognition in autonomous vehicles, and educational bots are presented to underline practical relevance. Performance metrics such as detection accuracy under varying lighting conditions, frame rate, and processing latency are analyzed to evaluate system robustness. This study concludes that color detection using camera modules enhances robotic adaptability and paves the way for more intelligent, vision-enabled machines.

Keywords: Color Detection, Computer Vision, OpenCV, HSV Color Space, Camera Module, Robotics, Raspberry Pi, Object Tracking