İnsansız Su Üstü Araçları için Uyarlanabilir Hedef Noktalarına Dayalı Kararlı bir Yol İzleme Algoritması
Abstract
Bu çalışma, insansız su üstü araçları için kararlı bir yol izleme algoritması önermektedir. Bu makalenin temel amacı, izleme hatalarını en aza indirmek için geliştirilmiş algoritmadaki bir anahtar parametreyi optimize etmektir. Bu parametreyi sınırlandırmak ve istikrarlı bir seyir yapmak için kararlılık kriteri belirlenmiştir. Bu model, önceki çalışmalarda kullanılan sabit değere karşılık optimum ve esnek parametreyi kullanarak her zaman adımı için benzersiz hedef noktalarını belirler. Önerilen kararlılık kriteri ve önceki zaman adımından elde edilen dönüş hızı verileri bu optimum parametreyi belirlemek için kullanılmaktadır. Bu çalışmada geliştirilen yöntem, keskin dönüş manevraları gibi kritik noktalarda daha düzgün bir seyrin gerçekleşmesini sağlar. Ayrıca, gerçekçi seyir yapmak için maksimum dönüş hızı için bir üst sınır içerir. Bu çalışmada önerilen model, geleneksel yol izleme algoritmasına kıyasla izleme hatalarını yaklaşık %20 oranında azaltmaktadır. Son olarak, diğer araştırmacıların çalışmalarını kolaylaştırmak için Matlab ortamında hazırlanan sayısal bir simulator, çalışmanın sonuna eklenmiştir.
References
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- Bibuli, M., Caccia, M., & Lapierre, L. (2007). Path-following algorithms and experiments for an autonomous surface vehicle. IFAC Proceedings Volumes, 40(17), 81-86.
- Campbell, S., Naeem, W., & Irwin, G. W. (2012). A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres. Annual Reviews in Control, 36(2), 267-283.
- Chung, S. H., Sah, B., & Lee, J. (2020). Optimization for drone and drone-truck combined operations: A review of the state of the art and future directions. Computers & Operations Research, 123, 105004.
- Conte, G., Duranti, S., & Merz, T. (2004). Dynamic 3D path following for an autonomous helicopter. IFAC Proceedings Volumes, 37(8), 472-477.
- Garcia, C. B. (1981). Pathways to solutions. Fixed Points and Equilibiria.
- Gould, F. J., & Tolle, J. W. (1983). Complementary pivoting on a pseudomanifold structure with applications in the decision sciences (Vol. 2). Heldermann.
- Gu, N., Wang, D., Peng, Z., Wang, J., & Han, Q. L. (2022). Advances in Line-of-Sight Guidance for Path Following of Autonomous Marine Vehicles: An Overview. IEEE Transactions on Systems, Man, and Cybernetics: Systems.
- Jin, X., Mei, W., & Zhaolong, Y. (2020, March). Path Following Control for Unmanned Aerial Vehicle Based on Carrot Chasing Algorithm and PLOS. In 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) (pp. 571-576). IEEE.
- Keller, H. B. (1987). Lectures on numerical methods in bifurcation problems. Applied Mathematics, 217, 50.
- Lee, S., Cho, A., & Kee, C. (2010). Integrated waypoint path generation and following of an unmanned aerial vehicle. Aircraft Engineering and Aerospace Technology.
- Liu, Z., Zhang, Y., Yu, X., & Yuan, C. (2016). Unmanned surface vehicles: An overview of developments and challenges. Annual Reviews in Control, 41, 71-93.
- Meenakshisundaram, V. S., Gundappa, V. K., & Kanth, B. S. (2010). Vector field guidance for path following of MAVs in three dimensions for variable altitude maneuvers. International Journal of Micro Air Vehicles, 2(4), 255-265.
- Miao, C. X., & Fang, J. C. (2012). An adaptive three-dimensional nonlinear path following method for a fix-wing micro aerial vehicle. International Journal of Advanced Robotic Systems, 9(5), 206.
- Naini, S. J. (2015). Optimal Line-of-Sight guidance law for moving targets. In 14th International Conference of Iranian Aerospace Society.
- Nelson, D. R., Barber, D. B., McLain, T. W., & Beard, R. W. (2007). Vector field path following for miniature air vehicles. IEEE Transactions on Robotics, 23(3), 519-529.
- Peng, Z., Wang, J., Wang, D., & Han, Q. L. (2020). An overview of recent advances in coordinated control of multiple autonomous surface vehicles. IEEE Transactions on Industrial Informatics, 17(2), 732-745.
- Perez-Leon, H., Acevedo, J. J., Millan-Romera, J. A., Castillejo-Calle, A., Maza, I., & Ollero, A. (2019, November). An aerial robot path follower based on the ‘carrot chasing’algorithm. In Iberian Robotics conference (pp. 37-47). Springer, Cham.
- Rheinboldt, W. C. (1986). Numerical analysis of parametrized nonlinear equations. Wiley-Interscience.
- Seydel, R. (1988). From Equilibrium to Chaos. Practical Bifurcation and Stability Analysis Elsevier Science Publishers.
- Shi, Y., Shen, C., Fang, H., & Li, H. (2017). Advanced control in marine mechatronic systems: A survey. IEEE/ASME Transactions on Mechatronics, 22(3), 1121-1131.
- Subbarao, K., & Ahmed, M. (2014). Nonlinear guidance and control laws for three-dimensional target tracking applied to unmanned aerial vehicles. Journal of Aerospace Engineering, 27(3), 604-610.
- Sujit, P. B., Saripalli, S., & Sousa, J. B. (2014). Unmanned aerial vehicle path following: A survey and analysis of algorithms for fixed-wing unmanned aerial vehicless. IEEE Control Systems Magazine, 34(1), 42-59.
- Todd, M. J. (2013). The computation of fixed points and applications (Vol. 124). Springer Science & Business Media.
- Zereik, E., Bibuli, M., Mišković, N., Ridao, P., & Pascoal, A. (2018). Challenges and future trends in marine robotics. Annual Reviews in Control, 46, 350-368.
Abstract
This study proposes a stable and robust path following algorithm for Unmanned Surface Vehicles (USVs). The main objective of this paper is to optimize a key parameter in the improved algorithm to minimize tracking errors. In this study, firstly a stability criterion is developed to limit this parameter and make stable navigation. This model determines the unique target points for each time step using the optimum and flexible parameter in contrast fixed value used in previous studies. The proposed stability criterion and the turning rate data obtained from the previous time step are used to determine this optimum parameter. It provides smooth and precise navigation at critical points like as sharp turning maneuvers. Moreover, it includes saturation for maximum turning rate to make realistic navigation. The proposed model in this study reduces tracking errors by around 20% compared to the conventional carrot-chasing algorithm. Finally, a numerical simulator for USVs in the Matlab environment has been included in the Appendix to support the work of other researchers.
References
- Allgower, E. L., & Georg, K. (1993). Continuation and path following. Acta numerica, 2, 1-64.
- Bibuli, M., Caccia, M., & Lapierre, L. (2007). Path-following algorithms and experiments for an autonomous surface vehicle. IFAC Proceedings Volumes, 40(17), 81-86.
- Campbell, S., Naeem, W., & Irwin, G. W. (2012). A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres. Annual Reviews in Control, 36(2), 267-283.
- Chung, S. H., Sah, B., & Lee, J. (2020). Optimization for drone and drone-truck combined operations: A review of the state of the art and future directions. Computers & Operations Research, 123, 105004.
- Conte, G., Duranti, S., & Merz, T. (2004). Dynamic 3D path following for an autonomous helicopter. IFAC Proceedings Volumes, 37(8), 472-477.
- Garcia, C. B. (1981). Pathways to solutions. Fixed Points and Equilibiria.
- Gould, F. J., & Tolle, J. W. (1983). Complementary pivoting on a pseudomanifold structure with applications in the decision sciences (Vol. 2). Heldermann.
- Gu, N., Wang, D., Peng, Z., Wang, J., & Han, Q. L. (2022). Advances in Line-of-Sight Guidance for Path Following of Autonomous Marine Vehicles: An Overview. IEEE Transactions on Systems, Man, and Cybernetics: Systems.
- Jin, X., Mei, W., & Zhaolong, Y. (2020, March). Path Following Control for Unmanned Aerial Vehicle Based on Carrot Chasing Algorithm and PLOS. In 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) (pp. 571-576). IEEE.
- Keller, H. B. (1987). Lectures on numerical methods in bifurcation problems. Applied Mathematics, 217, 50.
- Lee, S., Cho, A., & Kee, C. (2010). Integrated waypoint path generation and following of an unmanned aerial vehicle. Aircraft Engineering and Aerospace Technology.
- Liu, Z., Zhang, Y., Yu, X., & Yuan, C. (2016). Unmanned surface vehicles: An overview of developments and challenges. Annual Reviews in Control, 41, 71-93.
- Meenakshisundaram, V. S., Gundappa, V. K., & Kanth, B. S. (2010). Vector field guidance for path following of MAVs in three dimensions for variable altitude maneuvers. International Journal of Micro Air Vehicles, 2(4), 255-265.
- Miao, C. X., & Fang, J. C. (2012). An adaptive three-dimensional nonlinear path following method for a fix-wing micro aerial vehicle. International Journal of Advanced Robotic Systems, 9(5), 206.
- Naini, S. J. (2015). Optimal Line-of-Sight guidance law for moving targets. In 14th International Conference of Iranian Aerospace Society.
- Nelson, D. R., Barber, D. B., McLain, T. W., & Beard, R. W. (2007). Vector field path following for miniature air vehicles. IEEE Transactions on Robotics, 23(3), 519-529.
- Peng, Z., Wang, J., Wang, D., & Han, Q. L. (2020). An overview of recent advances in coordinated control of multiple autonomous surface vehicles. IEEE Transactions on Industrial Informatics, 17(2), 732-745.
- Perez-Leon, H., Acevedo, J. J., Millan-Romera, J. A., Castillejo-Calle, A., Maza, I., & Ollero, A. (2019, November). An aerial robot path follower based on the ‘carrot chasing’algorithm. In Iberian Robotics conference (pp. 37-47). Springer, Cham.
- Rheinboldt, W. C. (1986). Numerical analysis of parametrized nonlinear equations. Wiley-Interscience.
- Seydel, R. (1988). From Equilibrium to Chaos. Practical Bifurcation and Stability Analysis Elsevier Science Publishers.
- Shi, Y., Shen, C., Fang, H., & Li, H. (2017). Advanced control in marine mechatronic systems: A survey. IEEE/ASME Transactions on Mechatronics, 22(3), 1121-1131.
- Subbarao, K., & Ahmed, M. (2014). Nonlinear guidance and control laws for three-dimensional target tracking applied to unmanned aerial vehicles. Journal of Aerospace Engineering, 27(3), 604-610.
- Sujit, P. B., Saripalli, S., & Sousa, J. B. (2014). Unmanned aerial vehicle path following: A survey and analysis of algorithms for fixed-wing unmanned aerial vehicless. IEEE Control Systems Magazine, 34(1), 42-59.
- Todd, M. J. (2013). The computation of fixed points and applications (Vol. 124). Springer Science & Business Media.
- Zereik, E., Bibuli, M., Mišković, N., Ridao, P., & Pascoal, A. (2018). Challenges and future trends in marine robotics. Annual Reviews in Control, 46, 350-368.
Details
| Primary Language | English |
|---|---|
| Subjects | Maritime Engineering (Other) |
| Journal Section | Articles |
| Authors | |
| Early Pub Date | June 15, 2023 |
| Publication Date | June 15, 2023 |
| Published in Issue | Year 2023 Volume: 13 Issue: 2 |
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