论文信息 - 3D real-time path planning for AUV based on improved bio-inspired neural network

3D real-time path planning for AUV based on improved bio-inspired neural network

An improved algorithm based on bio-inspired neural network is proposed for Autonomous Underwater Vehicle (AUV) real-time path planning in three-dimensional (3D) environment in this paper. The algorithm has made an improvement in the shunting equation of the neural network model which is conductive to path planning especially in dynamic environments. The proposed approach has high efficiency and good real-time performance.

[1] Simon X. Yang,et al. Dynamic Task Assignment and Path Planning of Multi-AUV System Based on an Improved Self-Organizing Map and Velocity Synthesis Method in Three-Dimensional Underwater Workspace , 2013, IEEE Transactions on Cybernetics.

[2] Mohammad Pourmahmood Aghababa,et al. 3D path planning for underwater vehicles using five evolutionary optimization algorithms avoiding static and energetic obstacles , 2012 .

[3] Simon X. Yang,et al. Bioinspired Neural Network for Real-Time Cooperative Hunting by Multirobots in Unknown Environments , 2011, IEEE Transactions on Neural Networks.

[4] Stephen Grossberg,et al. Nonlinear neural networks: Principles, mechanisms, and architectures , 1988, Neural Networks.

[5] Javier Gilabert,et al. A biologically inspired neural network for navigation with obstacle avoidance in autonomous underwater and surface vehicles , 2011, OCEANS 2011 IEEE - Spain.