In order to improve the quality of the non-inferior solutions obtained by multi-objective particle swarm optimization (MOPSO), an improved algorithm called external archives self-searching multi-objective particle swarm optimization (EASS-MOPSO) was proposed and applied to a multi-objective trajectory optimization problem for manipulators. The position curves of joints were constructed by using quartic B-splines; the mathematical models of time, energy and jerk optimization objectives for manipulators were established; and the kinematic constraints of joints were transformed into the constraints of the control vertexes of the B-splines. A self-searching strategy of external archives to make non-inferior solutions have the ability to search the surrounding hyperspace was explored, and a diversity maintaining strategy of the external archives was proposed. The results of several test functions by simulation show that the convergence and diversity of the proposed algorithm are better than those of other 4 selected algorithms; the results of the trajectory optimization problem for manipulators by simulation show that the convergence, diversity and time consumption of the proposed algorithm are significantly better than those of non-dominated sorting genetic algorithm.

A Grid-Local Probability Road Map (PRM) method was proposed for the path planning of manipulators in dynamic environments. Based on the idea of boundary discretization, a double-grid model was built to obtain a mapping from dynamic obstacles to configuration space. The collision detection was simplified as a data indexing process to improve its efficiency. Times of collision detections were reduced by employing local programming strategies and the stratified sampling method. Moreover, the validity of sampling was increased. Taking the PUMA560 manipulator as a research object, the simulation experiments show that the time consumption of the proposed simplified collision-detection algorithm is about 14% of that of the standard one, and the stratified sampling is beneficial to the generation of probability maps compared with simple random sampling method. The simulation experiment of the static path planning shows that the proposed algorithm consumes an average of 10ms, which is superior to the comparison algorithm and has high efficiency and real-time performance. The simulation experiment of the dynamic path planning shows that the proposed algorithm consumes an average of 7ms per step, which is better than the comparison algorithm. The proposed algorithm can adjust the global path in real time to avoid obstacles as the environment changes. The algorithm mentioned has been proved to be efficient.INDEX TERMS Dynamic environment, double grid model, probability road map, path planning.

Direct dating of oil charge in superimposed basins is essential to understanding the evolutionary histories of petroleum systems, especially in sedimentary basins with complicated tectonic evolution and thermal histories. Based on analyses of different phases of calcite veins and primary oil inclusions, episodes of oil charge were determined by laser ablation−inductively coupled plasma−mass spectrometry (LA-ICP-MS) in situ U-Pb dating of calcite veins from an Ordovician reservoir within the Tahe Oilfield of the Tarim Basin, NW China. This basin has been subjected to multiple uplifts and erosions and repeated oil charges. The U-Pb dating results indicate that the first phase of oil charge occurred from 329.7 ± 1.6 Ma to 308.1 ± 4.1 Ma, and the second phase occurred from 249.3 ± 2.6 Ma to 220.5 ± 7.3 Ma. The timing of oil charge determined by fluid inclusion analysis alone can lead to great uncertainties due to the existence of multiple phases of oil charge and complex thermal evolution in superimposed basins. Our study demonstrates that U-Pb dating of calcite veins originating from the reservoirs offers a unique solution to determining the oil charge history, which avoids the multi-solution uncertainties in the timing of oil charge inferred from fluid inclusion analysis in superimposed basins.