MPC-based unified trajectory planning and tracking control approach for Automated Guided Vehicles∗
Autonomous navigation of Automated Guided Vehicles (AGVs) in manufacturing environment is an important part of industrial automation. This paper presents an MPC-based unified trajectory planning and tracking control approach for AGVs. Based on the model of the AGV, improved path planning and referen...
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sg-ntu-dr.10356-1444392020-11-05T06:47:26Z MPC-based unified trajectory planning and tracking control approach for Automated Guided Vehicles∗ Li, Juncheng Ran, Maopeng Wang, Han Xie, Lihua School of Electrical and Electronic Engineering 2019 IEEE 15th International Conference on Control and Automation (ICCA) Delta-NTU Corporate Laboratory Engineering::Computer science and engineering Automated Guided Vehicles Model Predictive Control Autonomous navigation of Automated Guided Vehicles (AGVs) in manufacturing environment is an important part of industrial automation. This paper presents an MPC-based unified trajectory planning and tracking control approach for AGVs. Based on the model of the AGV, improved path planning and reference velocity planning techniques are developed. Then a model predictive controller is designed to track the generated trajectory. In addition, obstacle avoidance capability is also incorporated in the navigation framework. To evaluate the proposed method, simulations and experiments are conducted. The results show that the AGV can achieve high trajectory tracking accuracy with smooth movement. Accepted version 2020-11-05T06:31:59Z 2020-11-05T06:31:59Z 2019 Conference Paper Li, J., Ran, M., Wang, H., & Xie, L. (2019). MPC-based unified trajectory planning and tracking control approach for Automated Guided Vehicles∗, Proceedings of the 2019 IEEE 15th International Conference on Control and Automation (ICCA), 374-380. doi:10.1109/ICCA.2019.8899955 9781728111643 https://hdl.handle.net/10356/144439 10.1109/ICCA.2019.8899955 2-s2.0-85075803603 374 380 en SMA-RP3 © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work is available at: https://doi.org/10.1109/ICCA.2019.8899955 application/pdf |
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Nanyang Technological University |
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Engineering::Computer science and engineering Automated Guided Vehicles Model Predictive Control |
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Engineering::Computer science and engineering Automated Guided Vehicles Model Predictive Control Li, Juncheng Ran, Maopeng Wang, Han Xie, Lihua MPC-based unified trajectory planning and tracking control approach for Automated Guided Vehicles∗ |
| description |
Autonomous navigation of Automated Guided Vehicles (AGVs) in manufacturing environment is an important part of industrial automation. This paper presents an MPC-based unified trajectory planning and tracking control approach for AGVs. Based on the model of the AGV, improved path planning and reference velocity planning techniques are developed. Then a model predictive controller is designed to track the generated trajectory. In addition, obstacle avoidance capability is also incorporated in the navigation framework. To evaluate the proposed method, simulations and experiments are conducted. The results show that the AGV can achieve high trajectory tracking accuracy with smooth movement. |
| author2 |
School of Electrical and Electronic Engineering |
| author_facet |
School of Electrical and Electronic Engineering Li, Juncheng Ran, Maopeng Wang, Han Xie, Lihua |
| format |
Conference or Workshop Item |
| author |
Li, Juncheng Ran, Maopeng Wang, Han Xie, Lihua |
| author_sort |
Li, Juncheng |
| title |
MPC-based unified trajectory planning and tracking control approach for Automated Guided Vehicles∗ |
| title_short |
MPC-based unified trajectory planning and tracking control approach for Automated Guided Vehicles∗ |
| title_full |
MPC-based unified trajectory planning and tracking control approach for Automated Guided Vehicles∗ |
| title_fullStr |
MPC-based unified trajectory planning and tracking control approach for Automated Guided Vehicles∗ |
| title_full_unstemmed |
MPC-based unified trajectory planning and tracking control approach for Automated Guided Vehicles∗ |
| title_sort |
mpc-based unified trajectory planning and tracking control approach for automated guided vehicles∗ |
| publishDate |
2020 |
| url |
https://hdl.handle.net/10356/144439 |
| _version_ |
1688665251517562880 |