This paper presents a new distributed positioning algorithm for unknown nodes in a wireless sensor network. The algorithm is based exclusively on connectivity. First, assuming that the positions of the anchor nodes ar...This paper presents a new distributed positioning algorithm for unknown nodes in a wireless sensor network. The algorithm is based exclusively on connectivity. First, assuming that the positions of the anchor nodes are already known, a circular belt containing an unknown node is obtained using information about the anchor nodes that are in radio range of the unknown node, based on the geometric relationships and communication constraints among the unknown node and the anchor nodes. Then, the centroid of the circular belt is taken to be the estimated position of the unknown node. Since the algorithm is very simple and since the only communication needed is between the anchor nodes and the unknown node, the communication and computational loads are very small. Furthermore, the algorithm is robust because neither the failure of old unknown nodes nor the addition of new unknown nodes influences the positioning of unknown nodes to be located. A theoretical analysis and simulation results show that the algorithm does not produce any cumulative error and is insensitive to range error, and that a change in the number of sensor nodes does not affect the communication or computational load. These features make this algorithm suitable for all sizes of low-power wireless sensor networks.展开更多
There is an ocean current in the actual underwater working environment. An improved self-organizing neural network task allocation model of multiple autonomous underwater vehicles(AUVs) is proposed for a three-dimensi...There is an ocean current in the actual underwater working environment. An improved self-organizing neural network task allocation model of multiple autonomous underwater vehicles(AUVs) is proposed for a three-dimensional underwater workspace in the ocean current. Each AUV in the model will be competed, and the shortest path under an ocean current and different azimuths will be selected for task assignment and path planning while guaranteeing the least total consumption. First, the initial position and orientation of each AUV are determined. The velocity and azimuths of the constant ocean current are determined. Then the AUV task assignment problem in the constant ocean current environment is considered. The AUV that has the shortest path is selected for task assignment and path planning. Finally, to prove the effectiveness of the proposed method, simulation results are given.展开更多
基金This work was supported by the National Science Foundation of P.R.China(No.60425310)the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of the Ministry of Education,P.R.China (TRAPOYT).
文摘This paper presents a new distributed positioning algorithm for unknown nodes in a wireless sensor network. The algorithm is based exclusively on connectivity. First, assuming that the positions of the anchor nodes are already known, a circular belt containing an unknown node is obtained using information about the anchor nodes that are in radio range of the unknown node, based on the geometric relationships and communication constraints among the unknown node and the anchor nodes. Then, the centroid of the circular belt is taken to be the estimated position of the unknown node. Since the algorithm is very simple and since the only communication needed is between the anchor nodes and the unknown node, the communication and computational loads are very small. Furthermore, the algorithm is robust because neither the failure of old unknown nodes nor the addition of new unknown nodes influences the positioning of unknown nodes to be located. A theoretical analysis and simulation results show that the algorithm does not produce any cumulative error and is insensitive to range error, and that a change in the number of sensor nodes does not affect the communication or computational load. These features make this algorithm suitable for all sizes of low-power wireless sensor networks.
基金Project supported by the National Natural Science Foundation of China(Nos.U1706224,91748117,and 51575336)the Creative Activity Plan for Science and Technology Commission of Shanghai,China(Nos.18JC1413000,18DZ1206305,and 16550720200)
文摘There is an ocean current in the actual underwater working environment. An improved self-organizing neural network task allocation model of multiple autonomous underwater vehicles(AUVs) is proposed for a three-dimensional underwater workspace in the ocean current. Each AUV in the model will be competed, and the shortest path under an ocean current and different azimuths will be selected for task assignment and path planning while guaranteeing the least total consumption. First, the initial position and orientation of each AUV are determined. The velocity and azimuths of the constant ocean current are determined. Then the AUV task assignment problem in the constant ocean current environment is considered. The AUV that has the shortest path is selected for task assignment and path planning. Finally, to prove the effectiveness of the proposed method, simulation results are given.
