Optimization of AGV Operation in the Dispatch Area Based on Reinforcement Learning Considering the Risk of Human-AGV Collision

Author:

Hwang Ingeun,Lee Hyun-Rok

Funder

Ministry of Science and ICT

National Research Foundation of Korea

Inha University

Publisher

Korean Institute of Industrial Engineers

Subject

General Medicine

Reference19 articles.

1. A survey of automation-enabled human-in-the-loop systems for infrastructure visual inspection

2. Cooperative zone-based rebalancing of idle overhead hoist transportations using multi-agent reinforcement learning with graph representation learning

3. Brockman, G., Cheung, V., Pettersson, L., Schneider, J., Schulman, J., Tang, J., and Zaremba, W. (2016), Openai gym, arXiv preprint arXiv:1606.01540.

4. A mathematical programming model for AGVS planning and control in manufacturing systems

5. Choi, H.-B., Kim, J.-B., Han, Y.-H., Oh, S.-W., and Kim, K.-H. (2022), Collision Avoidance Path Control of Multi-AGV Using Multi-Agent Reinforcement Learning, KIPS Transactions on Computer and Communication Systems, 11(9), 281-288.

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