Three-Dimensional Path Planning Based on Six-Direction Search Scheme.

In order to solve the problem of how to perform path planning for AUVs with multiple obstacles in a 3D underwater environment, this paper proposes a six-direction search scheme based on neural networks. In known environments with stationary obstacles, the obstacle energy is constructed based on a neural network and the path energy is introduced to avoid a too-long path being generated. Based on the weighted total energy of obstacle energy and path energy, a six-direction search scheme is designed here for path planning. To improve the efficiency of the six-direction search algorithm, two optimization methods are employed to reduce the number of iterations and total path search time. The first method involves adjusting the search step length dynamically, which helps to decrease the number of iterations needed for path planning. The second method involves reducing the number of path nodes, which can not only decrease the search time but also avoid premature convergence. By implementing these optimization methods, the performance of the six-direction search algorithm is enhanced in favor of path planning with multiple underwater obstacles reasonably. The simulation results validate the effectiveness and efficiency of the six-direction search scheme.

[Preliminary exploring of hyperspectral remote sensing experiment for nitrogen and phosphorus in water].

The content of nitrogen and phosphorus in the waters is an important index to measure water quality, and the technique of remote sensing plays a large role in monitoring the change in environment. The reflectance spectra of nitrogen and phosphorus with different concentrations were measured to discover their special features under pure water condition in the laboratory by hyperspectral remote sensing technique. The result shows that nitrogen has reflectance peaks at 404 and 477 nm, and phosphorus at 350 nm, and these reflectance peaks have a good correlation with their concentrations, then a quantitative retrieval model was deduced for nitrogen and phosphorus based on that. These results will lay an important basis for further monitoring nitrogen and phosphorus by remote sensing technique in the big inland lakes, reservoirs and rivers.

[Evaluating eutrophic state of Taihu Lake by in situ hyperspectra].

In situ experiments including water quality analyzing and spectra measuring were conducted on Jun., 2004 and Aug., 2004 in Taihu Lake for 21 samples. Then eutrophic state of Taihu Lake was evaluated by measured hyperspectra data, and the evaluating index was eutrophic state index (TSI). Firstly, the simulation model of water reflectance was built by analytic model using inherent optical properties (IOPs). Then Chlorophyll a content (Chl-a) was inversed by optimizing method by Matlab software; Secondly, TSI was calculated by inversed Chl-a, and the eutrophic state of Taihu Lake was evaluated by using ArcView' s interpolation function. The evaluation figures show that: there are notable differences between Jun., 2004 and Aug., 2004. The proportion of mesotropher state is as high as 61% in June, while the proportion of light eutrophic is as high as 52% in August. In totally, the most serious eutrophic state occurs in north of Taihu Lake. Eutrophlic state wears off from north to south. The lowest eutrophic region is in the east of Taihu Lake.