TY - GEN
T1 - Neural-network based AUV path planning in estuary environments
AU - Li, Shuai
AU - Guo, Yi
PY - 2012
Y1 - 2012
N2 - For the path planning problem of autonomous underwater vehicles (AUVs) in 3-dimensional (3-D) estuary environments, traditional methods may encounter problems due to their high computational complexity. In this paper, we proposed a dynamic neural network to solve the AUV path planning problem. In the neural network, neurons get input from the environment, locally interact with the neighbors and update neural activities in real time. The AUV path is then generated according to the neural activity landscapes. Stability, computational complexity of the neural network, and optimality of the generated path are analyzed. AUV path planning in 3-D complex environments without currents, with constant currents, and with variable currents are studied through simulations, which demonstrate the effectiveness of this approach.
AB - For the path planning problem of autonomous underwater vehicles (AUVs) in 3-dimensional (3-D) estuary environments, traditional methods may encounter problems due to their high computational complexity. In this paper, we proposed a dynamic neural network to solve the AUV path planning problem. In the neural network, neurons get input from the environment, locally interact with the neighbors and update neural activities in real time. The AUV path is then generated according to the neural activity landscapes. Stability, computational complexity of the neural network, and optimality of the generated path are analyzed. AUV path planning in 3-D complex environments without currents, with constant currents, and with variable currents are studied through simulations, which demonstrate the effectiveness of this approach.
KW - Neural networks
KW - autonomous underwater vehicle
KW - estuary environments
KW - path planning
UR - http://www.scopus.com/inward/record.url?scp=84872283727&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84872283727&partnerID=8YFLogxK
U2 - 10.1109/WCICA.2012.6359093
DO - 10.1109/WCICA.2012.6359093
M3 - Conference contribution
AN - SCOPUS:84872283727
SN - 9781467313988
T3 - Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
SP - 3724
EP - 3730
BT - WCICA 2012 - Proceedings of the 10th World Congress on Intelligent Control and Automation
T2 - 10th World Congress on Intelligent Control and Automation, WCICA 2012
Y2 - 6 July 2012 through 8 July 2012
ER -