Three-Dimensional Path Planning Method for Autonomous Underwater Vehicle Based on Modified Firefly Algorithm

Path planning is a classic optimization problem which can be solved by many optimization algorithms. The complexity of three-dimensional (3D) path planning for autonomous underwater vehicles (AUVs) requires the optimization algorithm to have a quick convergence speed. This work provides a new 3D path planning method for AUV using a modified firefly algorithm. In order to solve the problem of slow convergence of the basic firefly algorithm, an improved method was proposed. In the modified firefly algorithm, the parameters of the algorithm and the random movement steps can be adjusted according to the operating process. At the same time, an autonomous flight strategy is introduced to avoid instances of invalid flight. An excluding operator was used to improve the effect of obstacle avoidance, and a contracting operator was used to enhance the convergence speed and the smoothness of the path. The performance of the modified firefly algorithm and the effectiveness of the 3D path planning method were proved through a varied set of experiments.

[1]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[2]  Cai Guo-shan,et al.  Global Path Planning for AUV Based on Sparse A* Search Algorithm , 2012 .

[3]  Zhu Daqi.  Path planning for autonomous underwater vehicle based on artificial potential field method , 2010 .

[4]  Janez Brest,et al.  A Brief Review of Nature-Inspired Algorithms for Optimization , 2013, ArXiv.

[5]  Xin-She Yang,et al.  Firefly algorithm, stochastic test functions and design optimisation , 2010, Int. J. Bio Inspired Comput..

[6]  Janez Brest,et al.  A comprehensive review of firefly algorithms , 2013, Swarm Evol. Comput..

[7]  V. Mani,et al.  Exploring isospectral spring–mass systems with firefly algorithm , 2011, Proceedings of the Royal Society A.

[8]  Mohammad Reza Meybodi,et al.  An Improved Firefly Algorithm with Directed Movement , 2011 .

[9]  Theofanis Apostolopoulos,et al.  Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem , 2011 .

[10]  Ming-Huwi Horng,et al.  Multilevel Image Thresholding Selection Based on the Firefly Algorithm , 2010, 2010 7th International Conference on Ubiquitous Intelligence & Computing and 7th International Conference on Autonomic & Trusted Computing.

[11]  N. Chai-ead,et al.  Simulated Manufacturing Process Improvement via Particle Swarm Optimisation and Firefly Algorithms , 2011 .

[12]  Tomas Mauder,et al.  OPTIMIZATION OF THE QUALITY OF CONTINUOUSLY CAST STEEL SLABS USING THE FIREFLY ALGORITHM OPTIMIZACIJA KAKOVOSTI KONTINUIRNO LITE JEKLENE PLO(^E Z UPORABO ALGORITMA "FIREFLY" , 2011 .

[13]  Xin-She Yang,et al.  Firefly Algorithm, Lévy Flights and Global Optimization , 2010, SGAI Conf..

[14]  Sheng Shouzhao.  Route Planning Based on Particle Swarm Optimization with Threat Heuristic , 2011 .

[15]  Gan Xing-li.  Research on Global Path Planning of Underwater Vehicle Based on Ant Colony Algorithm , 2007 .

[16]  Leandro dos Santos Coelho,et al.  A chaotic firefly algorithm applied to reliability-redundancy optimization , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[17]  Zha Zhi.  Path Planning Based on Improved Genetic Algorithm for AUV , 2010 .

[18]  Iztok Fister,et al.  Firefly Algorithm: A Brief Review of the Expanding Literature , 2014 .

[19]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[20]  Xin-She Yang,et al.  Eagle Strategy Using Lévy Walk and Firefly Algorithms for Stochastic Optimization , 2010, NICSO.

[21]  Chang Liu,et al.  A New Path Planning Method Based on Firefly Algorithm , 2012, 2012 Fifth International Joint Conference on Computational Sciences and Optimization.

[22]  Dai Yun-tao,et al.  Path Planning of Underwater Vehicle in 3D Space Based on Ant Colony Algorithm , 2008 .

[23]  Mohammad Reza Meybodi,et al.  A Gaussian Firefly Algorithm , 2011 .