컨베이어식 자동 적재 로봇의 의사결정 지원을 위한 3차원 적재 알고리즘 개발

초록

The logistics industry is actively transitioning to unmanned systems and automation, propelled by advancements in AI and robotics. Amidst changing demographics and industrial dynamics, this shift emphasizes the imperative for logistics automation, with anticipated benefits such as reduced labor intensity and enhanced productivity in the transportation sector. This study focuses on a 3D vehicle loading space optimization algorithm designed to facilitate decision-making for the operation of conveyor-type automated loading robots. The algorithm takes into account various types of cargo, multi-destination scenarios, and environments with low-volume demand. It considers factors such as the spatial conditions of items, constraints on contact area, fragility, packaging types, and loading sequences based on delivery zones. Through this approach, we can derive coordinates for the placement of loaded items that satisfy the specified constraints. Numerical case validation demonstrate the effectiveness of our algorithm based on real-world data. The proposed algorithm has the potential to enhance logistics automation, providing flexibility to adapt to diverse logistics scenarios, thereby optimizing freight transport efficiency and contributing to the development of an eco-friendly logistics system.

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