Abstract
This paper focuses on a new approach of applying a pattern classification technique to ship routing plan. A safe path between a start point and a destination provides information about the space region partition. In the case of 2D routing plan, the route classifies the space into two districts. This means a dual problem of first classifying the entire space into two districts and then picking out the border as a route. We propose a novel approach to solve this dual problem based on support vector machine (SVM). SVM produces a non-linear separating surface on the basis of the margin maximization principle. This feature is applied to the objective of common routing plan problems, that is, generating a non-collision and smooth route. The effectiveness of the proposed approach is demonstrated by using several routing plan results in 2D spaces.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Avidan, S.: Support vector tracking. IEEE Trans. Pattern Anal. Mach. Intell. 26(8), 1064–1072 (2004). IEEE Press, New York
Caprin, S., Pillonetto, G.: Robot motion planning using adaptive random walks. In: Proceedings of 2003 IEEE International Conference on Robotics and Automation, pp. 3809–3814 (2003)
Lu, D.V., Hershberger, D., Smart, W.D.: Layered cost maps for context-sensitive navigation. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), pp. 709–715. IEEE Press, New York (2014)
Su, K.H., Lian, F.L., Yang, C.Y.: Navigation design with SVM path planning and fuzzy-based path tracking for wheeled agent. In: 2012 International Conference on Fuzzy Theory and it’s Applications, pp. 273–278 (2012)
Davoodi, M., Panahi, F., Mohades, A., Hashemi, S.N.: Clear and smooth path planning. Appl. Soft Comput. 32, 568–579 (2015)
Cossell, S., Guivant, J.: Concurrent dynamic programming for grid-based problems and its application for real-time path planning. Robot. Auton. Syst. 62, 737–751 (2014)
Do, Q.H., Mita, S., Nejad, H.T.N., Han, L.: Dynamic and safe path planning based on support vector machine among multi moving obstacles for autonomous vehicles. IEICE Trans. Inf. Syst. E96D, 314–328 (2013)
Miura, J.: Support vector path planning. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2894–2899. IEEE (2006)
Acknowledgements
This work was supported by the National Nature Science Foundation of China (Nos. 51579024, 61374114) and the Fundamental Research Funds for the Central Universities (DMU nos. 3132016311, 3132016005).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zhang, C., Guo, C. (2017). An Approach of Ship Routing Plan Based on Support Vector Machine. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2016. Communications in Computer and Information Science, vol 710. Springer, Singapore. https://doi.org/10.1007/978-981-10-5230-9_20
Download citation
DOI: https://doi.org/10.1007/978-981-10-5230-9_20
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5229-3
Online ISBN: 978-981-10-5230-9
eBook Packages: Computer ScienceComputer Science (R0)