Improving path planning efficiency for underwater gravity-aided navigation based on a new depth sorting fast search algorithm

This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results.

Applying systematic conservation planning to constitute a protection strategy for broad-leaved Korean pine forests in Changbai Mountains, China

The broad-leaved Korean pine(Pinus koraiensis) forest is one of the most biodiverse zonal communities in the North Temperate Zone and an important habitat for many endangered species.Broad-leaved Korean pine forests(BKPFs) are shrinking quickly due to deforestation and rapid urbanization. Thus, scientific protection strategies are urgently needed to change this status. Changbai Mountains contains one of the largest BKPFs and is considered a priority biodiversity conservation area in China. Guided by systematic conservation planning(SCP) methods and procedures, we chose representative species and communities in BKPFs ecosystem as priority conservation objects, and set quantitative conservation target, which is in the light of the biodiversity characteristic of BKPFs. The watershed area is used as planning unit. We used CPlan software to calculate the irreplaceability(Ir)value of each planning unit and the contribution value(Ti) of each conservation object to(1) assess the conservation efficiency;(2) identify the conservation gap of the existing conservation network. Then wecalculated a human disturbance index(HDI) for planning units in the conservation gaps and combine this with the Ir value to design three conservation scenarios to optimize the conservation network.Results show that planning units with high conservation value 14.16% of the total area, with3084.36 km2 were covered by the existing conservation network. 79.28% of planning units with high conservation value have not been protected which were concentrated mainly in the eight gap areas.Only 25.3% of protection objects achieved their conservation target with the existing conservation network. Conservation efficiency is low. Three conservation scenarios are constituted, each prioritizing a different aim:(1) ecological value;(2)species rescue; and(3) economical avoidance. The three conservation schemes potentially enable 93%,88% and 51% of conservation objects, respectively, to achieve identified conservation targets, thereby improving conservation efficiency significantly.