An Autonomous AI-Vision Robotic System with Mecanum Wheels for Real-Time Object Sorting and Navigation - Badri Mohapatra; Snehal Nalge; Tejas Sonale (Universitas Komputer Indonesia, 2025)
This study presents an autonomous robotic system combining AI vision, a Mecanum wheel-based mobile platform, and a servo-driven robotic arm for real-time object sorting and navigation in dynamic environments. The system employs an Arduino-based control framework with multi-sensor fusion (ultrasonic, infrared, and Bluetooth) to achieve obstacle avoidance, line following, and voice-command responsiveness. A novel color-based object classification algorithm is implemented, achieving a sorting accuracy of 94.2% for standardized packages in experimental trials. The Mecanum wheels enable omnidirectional mobility, reducing navigation time by 38% compared to conventional differential drives in constrained spaces. Experimental results demonstrate the system’s efficacy in smart manufacturing and automated logistics, offering a flexible, low-cost framework for scalable robotics