Autonomous Robot Navigation System Workflow for Monitoring and Maintenance in Industry 4.0 Applications
Main Article Content
Keywords
Computer Vision, Autonomous Navigation, Autonomous Mobile Robots, Automated Guided Vehicles, Robot Operating System
Abstract
Autonomous navigation in factories faces a different challenge with a lack of GPS, frequently changing environment, and human interference. Current methods employed include autonomous guided vehicles, which require extensive setup and lack flexibility, making it unsuitable for frequently changing environments. Prohibiting the adoption of an autonomous mobile robot is the slow mapping time and cost. A method of autonomous navigation combining computer vision with path-planning algorithms is presented. This method uses cameras attached to the environment for navigation and not on the robot to leverage security cameras commonly available. Out of the four aspects of navigation, only three were successful, namely perception, localisation, and cognition. Mapping via grayscale thresholding is found faster than simultaneous localisation and mapping but is less accurate because it is dependent on lighting. Faster region-based convolutional neural network or You Only Look Once version 4 (YOLOv4) found no difference because the travel time is significantly longer than the processing time of both. The proposed method using A* path planning with Euclidean heuristic successfully reaches the goal for at least 30 repeats. Navigational abilities are still limited in real-world settings because of accumulation of error from odometry and inertial measurement unit sensors and lack of localisation feedback.
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References
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Qiong, L., Xudong, C., Jizhuang, H., & Ruihao, M. (2020, 14-16 Aug. 2020). Research on Robot Path Planning Method Based on Tangent Intersection Method. 2020 International Conference on Information Science, Parallel and Distributed Systems (ISPDS). https://doi.org/10.1109/ISPDS51347.2020.00063
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Tan, L., Huangfu, T., Wu, L., & Chen, W. (2021). Comparison of yolo v3, faster r-cnn, and ssd for real-time pill identification. https://doi.org/10.21203/rs.3.rs-668895/v1
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Yang, S., Geng, C., Li, M., Liu, J., & Cui, F. (2022, 28-30 Oct. 2022). Improved Cartographer Algorithm Based on Map-to-Map Loopback Detection. 2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI). https://doi.org/10.1109/CVCI56766.2022.9964502
Yi, C., & Hongtu, X. (2019, 3-5 June 2019). Global Dynamic Path Planning Based on Fusion of Improved A* Algorithm and Morphin Algorithm. 2019 Chinese Control And Decision Conference (CCDC). https://doi.org/10.1109/CCDC.2019.8833360
Zaman, U. K. U., Aqeel, A. B., Naveed, K., Asad, U., Nawaz, H., & Gufran, M. (2021, 26-27 Oct. 2021). Development of Automated Guided Vehicle for Warehouse Automation of a Textile Factory. 2021 International Conference on Robotics and Automation in Industry (ICRAI). https://doi.org/10.1109/ICRAI54018.2021.9651360
Zhang, S., Liang, W., Yuan, X., An, H., Zheng, M., & Zhang, Y. (2023, 20-22 May 2023). A Robust Surveillance System for AGV Using Forward-Downward Visual Measurements. 2023 35th Chinese Control and Decision Conference (CCDC). https://doi.org/10.1109/CCDC58219.2023.10326630
Zhao, X., & Chidambareswaran, T. (2023, 26-30 Aug. 2023). Autonomous Mobile Robots in Manufacturing Operations. 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE). https://doi.org/10.1109/CASE56687.2023.10260631
Zheng, Z., Xie, M., Jiang, C., Bian, H., & Wang, W. (2024, 23-23 Aug. 2024). Indoor Mobile Robot Map Construction Based on Improved Cartographer Algorithm. 2024 WRC Symposium on Advanced Robotics and Automation (WRC SARA). https://doi.org/10.1109/WRCSARA64167.2024.10685767
Adkins, A., Chen, T., & Biswas, J. (2024). ObVi-SLAM: Long-Term Object-Visual SLAM. IEEE Robotics and Automation Letters, 9(3), 2909–2916. https://doi.org/10.1109/LRA.2024.3363534
Ahmadi, B., Vanany, I., & Dewi, R. S. (2023, 18-21 Dec. 2023). Smart Automated Guided Vehicles and Autonomous Mobile Robots in Warehouse Operations: A Bibliometric Analysis. 2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). https://doi.org/10.1109/IEEM58616.2023.10406697
Ahmed, A. J. O., Babiker, A., Elhag, A., & Drar, M. (2023, 28-30 Nov. 2023). Real-Time Agricultural Monitoring with Agrobot: A Raspberry Pi and YOLO Based Solution. 2023 International Conference on Computer and Applications (ICCA). https://doi.org/10.1109/ICCA59364.2023.10401368
Alatise, M. B., & Hancke, G. P. (2020). A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods. IEEE Access, 8, 39830–39846. https://doi.org/10.1109/ACCESS.2020.2975643
Campos, C., Elvira, R., Rodríguez, J. J. G., Montiel, J. M. M., & Tardós, J. D. (2021). ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual–Inertial, and Multimap SLAM. IEEE Transactions on Robotics, 37(6), 1874–1890. https://doi.org/10.1109/TRO.2021.3075644
Chen, C. W., Lin, C. L., Hsu, J. J., Tseng, S. P., & Wang, J. F. (2021, 16-17 Dec. 2021). Design and Implementation of AMR Robot Based on RGBD, VSLAM and SLAM. 2021 9th International Conference on Orange Technology (ICOT). https://doi.org/10.1109/ICOT54518.2021.9680621
Chen, L. B., Huang, X. R., & Chen, W. H. (2023). Design and Implementation of an Artificial Intelligence of Things-Based Autonomous Mobile Robot System for Pitaya Harvesting. IEEE Sensors Journal, 23(12), 13220–13235. https://doi.org/10.1109/JSEN.2023.3270844
Choi, J. H., Bae, S. H., An, Y. C., & Kuc, T. Y. (2023, 17-20 Oct. 2023). Development of an Advanced Navigation System for Autonomous Mobile Robots for Logistics Environments. 2023 23rd International Conference on Control, Automation and Systems (ICCAS). https://doi.org/10.23919/ICCAS59377.2023.10316962
Gunawan, R., Chandra, P. D., Kusmadi, Azwar, A. G., Nurwathi, & Risnanto, S. (2022, 13-14 Oct. 2022). Autonomous Vehicle Guided with RFID Position Detection for Warehouse Management System. 2022 16th International Conference on Telecommunication Systems, Services, and Applications (TSSA). https://doi.org/10.1109/TSSA56819.2022.10063925
Hess, W., Kohler, D., Rapp, H., & Andor, D. (2016, 16-21 May 2016). Real-time loop closure in 2D LIDAR SLAM. 2016 IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/ICRA.2016.7487258
Kaewpinjai, R., Chuaubon, T., & Apavatjrut, A. (2020, 24-27 June 2020). On Improving Indoor Navigation Accuracy Using Bluetooth Beacons. 2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). https://doi.org/10.1109/ECTI-CON49241.2020.9157901
Kim, J.-a., Sung, J.-Y., & Park, S.-h. (2020, 1-3 Nov. 2020). Comparison of Faster-RCNN, YOLO, and SSD for Real-Time Vehicle Type Recognition. 2020 IEEE International Conference on Consumer Electronics — Asia (ICCE-Asia). https://doi.org/10.1109/ICCE-Asia49877.2020.9277040
Kok, S. Y., Yu, W. W., & Ng, D. W. K. (2023, 21-23 April 2023). A Study on the Application of ORBSLAM3 on a Mobile Differential Drive Robot. 2023 8th International Conference on Control and Robotics Engineering (ICCRE). https://doi.org/10.1109/ICCRE57112.2023.10155617
Krishna, N. M., Reddy, R. Y., Reddy, M. S. C., Madhav, K. P., & Sudham, G. (2021, 2-4 Sept. 2021). Object Detection and Tracking Using Yolo. 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA). https://doi.org/10.1109/ICIRCA51532.2021.9544598
Kusashio, K., Yakoh, T., & Kakinuma, Y. (2024, 25-27 March 2024). Task Planning Optimization in Assisting Multiple NC Machine Tools Using AMR. 2024 IEEE International Conference on Industrial Technology (ICIT). https://doi.org/10.1109/ICIT58233.2024.10540943
Leong, P. Y., & Ahmad, N. S. (2024). Exploring Autonomous Load-Carrying Mobile Robots in Indoor Settings: A Comprehensive Review. IEEE Access, 12, 131395–131417. https://doi.org/10.1109/ACCESS.2024.3435689
Li, Z. X., Cui, G. H., Li, C. L., & Zhang, Z. S. (2021, 9-11 Oct. 2021). Comparative Study of Slam Algorithms for Mobile Robots in Complex Environment. 2021 6th International Conference on Control, Robotics and Cybernetics (CRC). https://doi.org/10.1109/CRC52766.2021.9620122
Mavilia, F., Barsocchi, P., Furfari, F., & Girolami, M. (2023, 30 Jan.-1 Feb. 2023). Evaluating the Impact of Anchors Deployment for an AoA-based Indoor Localization System. 2023 18th Wireless On-Demand Network Systems and Services Conference (WONS). https://doi.org/10.23919/WONS57325.2023.10061949
Merzlyakov, A., & Macenski, S. (2021, 27 Sept.-1 Oct. 2021). A Comparison of Modern General-Purpose Visual SLAM Approaches. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). https://doi.org/10.1109/IROS51168.2021.9636615
Neto, A. P., & Tonidandel, F. (2022, 29-30 April 2022). Analysis of WiFi localization techniques for kidnapped robot problem. 2022 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). https://doi.org/10.1109/ICARSC55462.2022.9784792
Niranjan, D., VinayKarthik, B., & Mohana. (2021, 15-17 Sept. 2021). Performance Analysis of SSD and Faster RCNN Multi-class Object Detection Model for Autonomous Driving Vehicle Research Using CARLA Simulator. 2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT). https://doi.org/10.1109/ICECCT52121.2021.9616712
Qiong, L., Xudong, C., Jizhuang, H., & Ruihao, M. (2020, 14-16 Aug. 2020). Research on Robot Path Planning Method Based on Tangent Intersection Method. 2020 International Conference on Information Science, Parallel and Distributed Systems (ISPDS). https://doi.org/10.1109/ISPDS51347.2020.00063
Roland, S., Illah Reza, N., & Davide, S. (2011). Mobile Robot Localization. In Introduction to Autonomous Mobile Robots (pp. 265–367). MIT Press. https://doi.org/10.1017/s0269888905210354
Shen, Y., Liu, J., & Luo, Y. (2021, 17-19 Dec. 2021). Review of Path Planning Algorithms for Unmanned Vehicles. 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA). https://doi.org/10.1109/ICIBA52610.2021.9688064
Tan, L., Huangfu, T., Wu, L., & Chen, W. (2021). Comparison of yolo v3, faster r-cnn, and ssd for real-time pill identification. https://doi.org/10.21203/rs.3.rs-668895/v1
Wang, C., & Mao, J. (2019, 18-20 Oct. 2019). Summary of AGV Path Planning. 2019 3rd International Conference on Electronic Information Technology and Computer Engineering (EITCE). https://doi.org/10.1109/EITCE47263.2019.9094825
Yang, S., Geng, C., Li, M., Liu, J., & Cui, F. (2022, 28-30 Oct. 2022). Improved Cartographer Algorithm Based on Map-to-Map Loopback Detection. 2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI). https://doi.org/10.1109/CVCI56766.2022.9964502
Yi, C., & Hongtu, X. (2019, 3-5 June 2019). Global Dynamic Path Planning Based on Fusion of Improved A* Algorithm and Morphin Algorithm. 2019 Chinese Control And Decision Conference (CCDC). https://doi.org/10.1109/CCDC.2019.8833360
Zaman, U. K. U., Aqeel, A. B., Naveed, K., Asad, U., Nawaz, H., & Gufran, M. (2021, 26-27 Oct. 2021). Development of Automated Guided Vehicle for Warehouse Automation of a Textile Factory. 2021 International Conference on Robotics and Automation in Industry (ICRAI). https://doi.org/10.1109/ICRAI54018.2021.9651360
Zhang, S., Liang, W., Yuan, X., An, H., Zheng, M., & Zhang, Y. (2023, 20-22 May 2023). A Robust Surveillance System for AGV Using Forward-Downward Visual Measurements. 2023 35th Chinese Control and Decision Conference (CCDC). https://doi.org/10.1109/CCDC58219.2023.10326630
Zhao, X., & Chidambareswaran, T. (2023, 26-30 Aug. 2023). Autonomous Mobile Robots in Manufacturing Operations. 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE). https://doi.org/10.1109/CASE56687.2023.10260631
Zheng, Z., Xie, M., Jiang, C., Bian, H., & Wang, W. (2024, 23-23 Aug. 2024). Indoor Mobile Robot Map Construction Based on Improved Cartographer Algorithm. 2024 WRC Symposium on Advanced Robotics and Automation (WRC SARA). https://doi.org/10.1109/WRCSARA64167.2024.10685767
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Dec 30, 2024
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Cornelius, S. P., Ong, J. J., Chiew, T. H., Chang, K. M., & Lee, Y. K. (2024). Autonomous Robot Navigation System Workflow for Monitoring and Maintenance in Industry 4.0 Applications. Journal of Telecommunications and the Digital Economy, 12(4), 85–108. https://doi.org/10.18080/jtde.v12n4.1017
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Digital Economy & Society
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