Autonomous Material Handling Systems in Smart Factories: Advanced Path Planning and Control of Industrial Robots for Manufacturing Applications

ABSTRACT

The evolution of smart factories within Industry 4.0 is fundamentally dependent on the seamless and intelligent movement of materials. Autonomous Material Handling Systems, particularly those employing advanced industrial robots, have transitioned from fixed automation to flexible, intelligent agents central to cyber-physical production systems. This article presents a comprehensive examination of the state of the art, challenges, and future directions in path planning and control algorithms for industrial robots deployed in material handling applications within smart manufacturing environments. Through a systematic literature review and analysis of emerging empirical research, it investigates the integration of real-time sensory data, the demands of dynamic and unstructured environments, and the necessity for robust, adaptive control strategies. For the manipulator payload variation test, the adaptive controller reduced the average tracking error by 65% compared to the nominal MPC and recovered stable tracking 70% faster following a payload change. Timed Elastic Band (TEB) recorded 95% success followed by Dynamic Window Approach (DWA) 92% success while A (Global only) was only 12%. The adaptive and learning-augmented controllers successfully compensated, maintaining safe distances in all trials, though the learning controller required prior experience with similar disturbance magnitudes. The discourse highlights the critical gap between theoretical algorithmic advancements in controlled settings and their practical, reliable deployment in complex, real-world factory floors. This article concludes by proposing a multi-layered framework for next-generation autonomous material handling and outlines specific research trajectories to bridge existing gaps between simulation and reality.

Keywords — Autonomous Mobile Robots (AMRs), Path Planning, Motion Control, Smart Factory,

Industry 4.0, Material Handling, Cyber-Physical Systems, Multi-Robot Systems.