Research on Multi-robot Material Picking and Autonomous Path Planning System in Industrial Environment

This study looks at how to improve material handling and autonomous navigation in modern smart factories. To tackle the problems of coordinating many robots and picking items accurately in tight industrial spaces, we propose a combined system that pairs a transfer robot with a robotic arm. The navigation part uses a tweaked A* path‑planning algorithm called Hierarchical Cooperative A* (HCA). HCA lets several mobile robots work together while avoiding collisions and deadlocks in narrow warehouse aisles. For the picking task, a mechanical arm controlled by a proportional‑integral‑derivative (PID) controller is mounted on the robot’s base. The arm can grasp and lift objects reliably. We test the system by measuring three

things: how efficient the paths are, how well it avoids collisions, and how accurately it follows planned trajectories, all under simulated industrial constraints. The approach offers a clear way to scale up autonomous transfer operations in large logistics and manufacturing plants. Future work will shift from discrete to continuous action spaces and add advanced computer‑vision feedback, making the arm more adaptable and precise during dynamic grasping.

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