Open Access Open Access  Restricted Access Subscription or Fee Access

Robotic Warehouse Management System

(*) Corresponding author

Authors' affiliations



This study presents two approaches to the prevention of inter-robot collisions. The first approach is to develop trajectory planning and motion control algorithms. The second approach is to reduce the number of auxiliary robots as much as possible. The rigidly programmed systems are less flexible and adaptive than systems capable of independent data analysis and pattern identification. Therefore, this study uses the neural network for robot training and an analytical module (AN) to make decisions regarding the quantity of robots. The AN assisted and non-assisted management systems were examined under the two scenarios, namely the steady and random increment of applications. In both scenarios, using the AN reduced the number of auxiliary robots and, consequently, robot collisions in the operating area. This can help to reduce the warehouse maintenance costs and improve manufacturing scalability. Therefore, the proposed robotic management system has the potential to enhance warehouse efficiency.
Copyright © 2021 Praise Worthy Prize - All rights reserved.


Warehouse Management System; Control System; Robotic Device; Neural Networks; Energy Consumption; Microservice Architecture

Full Text:



M. Kunz, S. Ó hÉigeartaigh, Artificial Intelligence and Robotization. Artificial Intelligence and Robotization (November 21, 2018), in Oxford Handbook on the International Law of Global Security (Oxford University Press, 2018, pp. 1-16).

F. Chiacchio, G. Petropoulos, D. Pichler, The impact of industrial robots on EU employment and wages: A local labour market approach (No. 2018/02). (Bruegel working paper, 2018).

Win, T., Hesketh, T., Eaton, R., Robotic Tower Crane Modeling and Control (RTCMC) with LQR-DRO and LQR-LEIC for Linear and Nonlinear Payload Swing Minimization, (2016) International Review of Automatic Control (IREACO), 9 (2), pp. 72-87.

R. Bogue, What are the prospects for robots in the construction industry? Industrial Robot, Vol. 45(Issue 1): 1-6, 2018.

Ababneh, M., Sha'ban, H., AlShater, A., AbuHamdan, B., AlKafaween, M., AlMansour, S., Design of a Gesture Controlled Mobile Robotic Arm, (2018) International Review of Automatic Control (IREACO), 11 (1), pp. 36-43.

R. Farel, S. Kchir, X. Lamy, M. Grossard, Challenges in Sustainable Manufacturing With Industrial and Collaborative Robots: A Case Study, In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Vol. 51791, p. V004T05A040, American Society of Mechanical Engineers, 2018.

C. Schou, R.S. Andersen, D. Chrysostomou, S. Bøgh, O. Madsen, Skill-based instruction of collaborative robots in industrial settings, Robotics and Computer-Integrated Manufacturing, Vol 53: 72-80, 2018.

R. Hadidi, J. Cao, M. Woodward, M.S. Ryoo, H. Kim, Distributed perception by collaborative robots, IEEE Robotics and Automation Letters, Vol. 3(Issue 4): 3709-3716, 2018.

G. Raiola, C.A. Cardenas, T.S. Tadele, T. De Vries, S. Stramigioli, Development of a safety-and energy-aware impedance controller for collaborative robots, IEEE Robotics and automation letters, Vol. 3(Issue 2): 1237-1244, 2018.

A. Olivares-Alarcos, S. Foix, G. Alenya, On inferring intentions in shared tasks for industrial collaborative robots, Electronics, Vol. 8(Issue 11): 1306, 2019.

A. Hanna, P.L. Götvall, M. Ekström, K. Bengtsson, Requirements for designing and controlling autonomous collaborative robots system-an industrial case, In Advances in Transdisciplinary Engineering, pp. 139-144, IOS Press, 2018.

K.C. Vivaldini, J.P. Galdames, T.S. Bueno, R.C. Araújo, R.M. Sobral, M. Becker, G.A. Caurin, Robotic forklifts for intelligent warehouses: Routing, path planning, and auto-localization, In Proceedings of the IEEE International Conference on Industrial Technology, Vol. 5472487, pp. 1463-1468, IEEE, 2010.

A.M. Atieh, H. Kaylani, Y. Al-abdallat, A. Qaderi, L. Ghoul, L. Jaradat, I. Hdairis, Performance improvement of inventory management system processes by an automated warehouse management system, Procedia Cirp, Vol. 41: 568-572, 2016.

C.K.M. Lee, Y. Lv, K.K.H. Ng, W. Ho, K.L. Choy, Design and application of Internet of things-based warehouse management system for smart logistics, International Journal of Production Research, Vol. 56(Issue 8): 2753-2768, 2018.

J. Mao, H. Xing, X. Zhang, Design of intelligent warehouse management system, Wireless Personal Communications, Vol. 102(Issue 2): 1355-1367, 2018.

A. Anđelković, M. Radosavljević, Improving order-picking process through implementation of warehouse management system, Strategic Management, Vol. 23(Issue 1): 3-10, 2018.

C.S. Choong, A.F.A. Nasir, A.P.A Majeed, M.A. Zakaria, M.A.M. Razman, Automatic identification and Categorize Zone of RFID reading in Warehouse Management System, In Advances in Mechatronics, Manufacturing, and Mechanical Engineering (Springer, Singapore, 2020, pp. 194-206).

M. Makaci, P. Reaidy, K. Evrard-Samuel, V. Botta-Genoulaz, T. Monteiro, Pooled warehouse management: An empirical study, Computers & Industrial Engineering, Vol. 112: 526-536, 2017.

M.R. Davies, Deskilling Robots in Logistics Environments, KünstlIntell, Vol. 33: 407-410, 2019.

G.Q. Huang, M.Z.Q. Chen, J. Pan, Robotics in ecommerce logistics, HKIE Transactions Hong Kong Institution of Engineers, Vol. 22(Issue 2): 68-77, 2015.

L. De Lauretis, From Monolithic Architecture to Microservices Architecture, In IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), pp. 93-96, IEEE, 2019.

M. Al-Emran, H.A. Chalabi, Developing an IT Help Desk Troubleshooter Expert System for diagnosing and solving IT Problems, In Proceedings of the 2nd BCS International IT Conference 2014, pp. 1-5, BCSIIT, 2014.

J. Ghommam, N. Derbel, Q. Zhu, New Trends in Robot Control (Springer Singapore, 2020).

T. Blanchard, B. Samanta, Wind speed forecasting using neural networks, Wind Engineering, Vol. 44(Issue 1): 33-48, 2020.

G. Celenta, D. Guida, Object Recognition Using Neural Networks for Robotics Precision Application, in Design, Simulation, Manufacturing: The Innovation Exchange (Springer, Cham, 2020, pp. 108-117).

J. Xu, R. Rahmatizadeh, L. Bölöni, D. Turgut, Real-time prediction of taxi demand using recurrent neural networks, IEEE Transactions on Intelligent Transportation Systems, Vol. 19(Issue 8): 2572-2581, 2017.

W. Yong, L. Qing, W. Lei, S. Hao, Improvement of RFID locating algorithm in warehouse security system, In 2017 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI), pp. 190-195, IEEE, 2017.

P.R. Teja, A.N. Kumaar, QR Code based Path Planning for Warehouse Management Robot, In 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1239-1244, IEEE, 2018.

P. Dharmasiri, I. Kavalchuk, M. Akbari, Novel Implementation of Multiple Automated Ground Vehicles Traffic Real Time Control Algorithm for Warehouse Operations: Djikstra Approach, Operations and Supply Chain Management: An International Journal, Vol. 13(Issue 4): 396-405, 2020.

El Kari, B., Ayad, H., El Kari, A., Mjahed, M., Pozna, C., Design and FPGA Implementation of a New Intelligent Behaviors Fusion for Mobile Robot Using Fuzzy Logic, (2019) International Review of Automatic Control (IREACO), 12 (1), pp. 1-10.

A. Ospanov, A. Timurbekova, New hypothesis of energy of crushing. Journal of Hygienic Engineering and Design, Vol. 27: 87-89, 2019.

Y. Fang, J. Hu, W. Liu, Q. Shao, J. Qi, Y. Peng, Smooth and time-optimal S-curve trajectory planning for automated robots and machines, Mechanism and Machine Theory, Vol. 137: 127-153, 2019.

S. Kucuk, Optimal trajectory generation algorithm for serial and parallel manipulators, Robotics and Computer-Integrated Manufacturing, Vol. 48: 219-232, 2017.

Tynchenko, V., Milov, A., Tynchenko, V., Bukhtoyarov, V., Kukartsev, V., Intellectualizing the Process of Waveguide Tracks Induction Soldering for Spacecrafts, (2019) International Review of Aerospace Engineering (IREASE), 12 (6), pp. 280-289.

Al-Qaisi, A., Manasreh, A., Sharadqeh, A., Alqadi, Z., Digital Color Image Classification Based on Modified Local Binary Pattern Using Neural Network, (2019) International Journal on Communications Antenna and Propagation (IRECAP), 9 (6), pp. 403-408.


  • There are currently no refbacks.

Please send any question about this web site to
Copyright © 2005-2024 Praise Worthy Prize