Sailboat navigation control system based on spiking neural networks
Nelson Santiago Giraldo
Sebastián Isaza
Ricardo Andrés Velásquez
Department of Electronics and Telecommunications Engineering,University of Antioquia,67 st,Medellin 050010,Antioquia,Colombia
摘要：In this paper,we presented the development of a navigation control system for a sailboat based on spiking neural networks(SNN).Our inspiration for this choice of network lies in their potential to achieve fast and low-energy computing on specialized hardware.To train our system,we use the modulated spike time-dependent plasticity reinforcement learning rule and a simulation environment based on the BindsNET library and USVSim simulator.Our objective was to develop a spiking neural network-based control systems that can learn policies allowing sailboats to navigate between two points by following a straight line or performing tacking and gybing strategies,depending on the sailing scenario conditions.We presented the mathematical definition of the problem,the operation scheme of the simulation environment,the spiking neural network controllers,and the control strategy used.As a result,we obtained 425 SNN-based controllers that completed the proposed navigation task,indicating that the simulation environment and the implemented control strategy work effectively.Finally,we compare the behavior of our best controller with other algorithms and present some possible strategies to improve its performance.
机标关键词：controlsystembasednavigationnetworksneuralsailboatspiking
论文发表日期：2023-11-05
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：16( 489-504 )
英文信息