Abstract

The rapid advancement of automation technologies and the increasing demand for precision-driven industrial processes have significantly accelerated the adoption of mobile robots in pick-and-place applications. These robots equipped with automated guidance systems have transformed traditional manufacturing warehousing logistics and material handling environments by providing high operational efficiency reduced labor dependence and consistent accuracy. Pick-and-place activities—once completed manually—are now performed through intelligent robotic mechanisms that integrate sensors actuators machine vision navigation algorithms and autonomous decision-making systems. Automated Guided Mobile Robots (AGMRs) are designed to interpret environmental conditions identify objects compute optimized paths avoid collisions and execute repetitive tasks with minimal human intervention. Through a combination of embedded controllers path-planning algorithms SLAM techniques and real-time feedback mechanis