Academic Journal of Engineering and Technology Science, 2024, 7(2); doi: 10.25236/AJETS.2024.070210.
Peng Liu1, Zhipeng Xie2, Ang He2, Linjun Fu2, Baiheng Tang3
1College of Transport & Communications, Shanghai Maritime University, Shanghai, China
2College of Information Engineering, Shanghai Maritime University, Shanghai, China
3Merchant Marine College, Shanghai Maritime University, Shanghai, China
In the process of transporting commodity by sea, the ship clearance of general cargo ship has always been a hassle for the crew. Under a tight schedule and heavy task chart, it is frequently essential to work day and night upside down for crew to accomplish the cleaning of the cabin and unloading work. Sometimes it may not even be possible to complete unloading and clearance in time, resulting in massive economic losses. In this paper, a multi-functional ship clearance and sorting robot model is proposed based on the actual environment of the cargo ship's hold, which can not only realize the sorting of goods, but also assist in the cleaning of the ship hold after unloading. We have combined a robotic arm, a relevant target recognition algorithm and an Automatic Guided Vehicle(AGV) chassis which equipped with a Simultaneous Localization and Mapping (SLAM) algorithm to realize this robot, Collaborate with each other through the Robot Operating System(ROS) system. Experimental trials show that our robot is more accurate in positioning in the cabin environment compared to other algorithms, and has the preliminary function of cleaning the cabins of general cargo ships as a potential intelligent future trend, it may be useful for ship clearance functions. This project can be applied to the above scenarios or other similar areas. This article also compared two classic SLAM algorithms: hector slam and gmapping, and ultimately concluded that hector slam is more suitable for the above environment.
Ship clearance, Automatic sorting, Robot, Cargo, Automated guided vehicles(AGV)
Peng Liu, Zhipeng Xie, Ang He, Linjun Fu, Baiheng Tang. A multifunctional ship sorting and clearance robot implementation model. Academic Journal of Engineering and Technology Science (2024) Vol. 7, Issue 2: 56-62. https://doi.org/10.25236/AJETS.2024.070210.
[1] Yue Wenlong Research on Point Cloud Processing Algorithm for Port Automatic Unloading System [D]. Shanghai Jiao Tong University, 2020. DOI: 10.27307/d.cnki. gsjtu.2019.002621(In Chinese).
[2] Checcucci Enrico, Piramide Federico, De Cillis Sabrina, et al. Health Information Technology Usability Evaluation Scale and User-Experience Questionnaire for 3D Intraoperative Cognitive Navigation System for Urological Procedures[J]. Medicina, 2023, 59(3):624-624.
[3] Yunze, L. Research on SLAM of Indoor Robot Based on Lidar. Master’s Thesis, South China University of Technology, Guangzhou, China, 2016.
[4] Zhao J, Liu S, Li J. Research and Implementation of Autonomous Navigation for Mobile Robots Based on SLAM Algorithm under ROS. Sensors. 2022; 22(11):4172. https://doi.org/10.3390/s22114172
[5] Wenzhi, L. Research and Implementation of SLAM and Path Planning Algorithm Based on Lidar. Master’s Thesis, Harbin Institute of Technology, Harbin, China, 2018.
[6] Z. Yong et al., "An Autonomous Navigation Strategy Based on Improved Hector SLAM With Dynamic Weighted A* Algorithm," in IEEE Access, vol. 11, pp. 79553-79571, 2023, doi: 10.1109/ACCESS.2023.3299293.
[7] C. Tian, H. Liu, Z. Liu, H. Li and Y. Wang, "Research on Multi-Sensor Fusion SLAM Algorithm Based on Improved Gmapping," in IEEE Access, vol. 11, pp. 13690-13703, 2023, doi: 10.1109/ACCESS.2023.3243633.
[8] Gao C. et al 2019 Research on a Panoramic Mobile Robot for Autonomous Navigation Proc. of the 3rd Int. Conf. on Mechatronics Engineering and Information Technology 87 204-207
[9] Zhang B, Li S, Qiu J, You G, Qu L. Application and Research on Improved Adaptive Monte Carlo Localization Algorithm for Automatic Guided Vehicle Fusion with QR Code Navigation. Applied Sciences. 2023; 13(21):11913. https://doi.org/10.3390/app132111913
[10] W. Hess, D. Kohler, H. Rapp and D. Andor, "Real-time loop closure in 2D LIDAR SLAM," 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016, pp. 1271-1278, doi: 10.1109/ICRA.2016.7487258.