Mesoscale oceanic eddies in the South China Sea from 1992 to 2012:evolution processes and statistical analysis

Automated identification and tracking of mesoscale ocean eddies has recently become one research hotspot in physical oceanography. Several methods have been developed and applied to survey the general kinetic and geometric characteristics of the ocean eddies in the South China Sea（SCS）. However, very few studies attempt to examine eddies＇ internal evolution processes. In this study, we reported a hybrid method to trace eddies＇ propagation in the SCS based on their internal structures, which are characterized by eddy centers, footprint borders, and composite borders. Eddy identification and tracking results were represented by a GIS-based spatiotemporal model. Information on instant states, dynamic evolution processes, and events of disappearance, reappearance, split, and mergence is stored in a GIS database. Results were validated by comparing against the ten Dongsha Cyclonic Eddies（DCEs） and the three long-lived anticyclonic eddies（ACEs） in the northern SCS, which were reported in previous literature. Our study confirmed the development of these eddies. Furthermore, we found more DCE-like and ACE-like eddies in these areas from 2005 to 2012 in our database. Spatial distribution analysis of disappearing, reappearing, splitting, and merging activities shows that eddies in the SCS tend to cluster to the northwest of Luzon Island, southwest of Luzon Strait, and around the marginal sea of Vietnam. Kuroshio intrusions and the complex sea floor topography in these areas are the possible factors that lead to these spatial clusters.

Real-time dynamic system to path tracking and collision avoidance for redundant robotic arms

An dynamic system for real-time obstacle avoidance path planning of redundant robots is constructed in this paper. Firstly, the inter-frame difference method is used to identify the moving target and to calculate the target area, then on the basis of color features and gradient features extracted from the target area, the feature fusion Cam-Shift mean shift algorithm is used to track target, improving the robustness of the tracking algorithm. Secondly, a parallel two-channel target identification and location method based on binocular vision is proposed, updating the target＇s three-dimensional information in real time. Then, a dynamic collision-free path planning method is implemented： the safety rods are removed through the intersection test, and the minimum distance is derived directly by using the coordinate values of the target in the local coordinate system of the rod. On this basis, the obstacle avoidance gain and escape velocity related to the minimum distance is established, and obstacle avoidance path planning is implemented by using the zero space mapping matrix of redundant robot. Experiments are performed to Study the efficiency of the proposed system.