Abstract

This paper addresses the material handling problem (MHS) in warehouse automation by proposing a system that uses an automated guided vehicle (AGV) in industrial environments. The aim is to optimize the picking task with respect to manual operation in a paint factory. The work describes the whole system to perform all the automatic tasks. The process is controlled by the Manufacturing Process Management System (MPMS) and an autonomous co-worker robot execute the mission in partially known environments. The navigation system implemented is safe and robust. It considers the people detection and unknown static obstacles. Also, an ultra-wide-band localization system is implemented by offering new capabilities for situation awareness in factories. Experiments with a real holonomic platform called ARCO are performed to validate the approach.

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