Journal
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
Volume 10, Issue 2, Pages 304-313Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCDS.2017.2727678
Keywords
Autonomous underwater vehicles (AUVs); biologically inspired self-organizing map (BISOM); obstacle avoidance; speed jump; task assignment and path planning
Funding
- National Natural Science Foundation of China [51575336, U170620065]
- National Key Project of Research and Development Program [2017YFC0306302]
- Creative Activity Plan for Science and Technology Commission of Shanghai [16550720200]
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An integrated biologically inspired self-organizing map (SOM) algorithm is proposed for task assignment and path planning of an autonomous underwater vehicle (AUV) system in 3-D underwater environments with obstacle avoidance. The algorithm embeds the biologically inspired neural network (BINN) into the SOM neural networks. The task assignment and path planning aim to arrange a team of AUVs to visit all appointed target locations, while assuring obstacle avoidance without speed jump. The SOM neuron network is developed to assign a team of AUVs to achieve multiple target locations in underwater environments. Then, in order to avoid obstacles and speed jump for each AUV that visits the corresponding target location, the BINN is utilized to update weights of the winner of SOM, and achieve AUVs path planning and effective navigation. The effectiveness of the proposed hybrid model is validated by simulation studies.
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