Research On Path Planning Primary Technology For Cobalt-rich Crust Mining Vehicles In Deep-sea

Deep-sea cobalt-rich crust is a kind of resource grown on seabed in500-3000m deep, which contain many rare metals such as cobalt, platinum, and also contain manganese, nickel, iron, copper and other metals. It is a kind of important mineral resource. With rapidly reducing of resources on land, as a kind of marine mineral resource with extremely commercial value to exploit, deep-sea cobalt-rich crust is catching attentions of USA, Germany, Japan, Russia and other western countries. Some countries have entered into trial mining stage with gradual deepening research on mining and exploration of cobalt-rich crust. Compared with western developed countries, In China, Research on cobalt-rich crust mining and exploration was carried out later. To safeguard the marine rights of China, and open up new mineral resource in our country, and face the situation of striving marine resources in international community, it is necessary to carry out research on cobalt-rich crust mining, exploration and equipment.This paper is supported by item DY105-03-02(Research on Key Technology and Equipment of Cobalt-rich Crust Mining Model Vehicle). After consulting a large quantity of related research papers and technique reports, the author is carried out thorough and systemic study on deep-sea world modeling problem, deep-sea large-scale traversal path planning problem, deep-sea static path planning problem and deep-sea dynamic path planning problem. Main research results are as follows:1) A kind of world modeling model with different types of bottom materials in highly unstructured seafloor environment was proposed. DEM data with bottom material class attributes detected in prophase was utilized, by extracting terraingeometrical characteristic, four-dimensional mixed attributes data of seafloor environment was obtained. Terrain trafficability index with different class was got by using the fuzzy reasoning method. By setting up comprehensive trafficability cost function, terrain trafficabilities in seafloor environment with different bottom materials were normalized, and then the world trafficability map was obtained. This model could provide a modeling foundation for study on path planning. The efficiency of the method was verified by and simulations experiments.2) A large scale traverse path planning method in mineral domain was put forward. Firstly traverse path planning performance evaluation function was set. Through the calculation of evaluation function, the way of reciprocating mining method was determined. The world model was divided into some subdomains by using Boustrophedon method. Comprehensive connection distance matrix for subdomains was set up, then the problem of connection among subdomains could be turned into TSP. After solved the problem through ACO, the optimal objective of maximum coverage was achieved. Transfered local path searching problem among no-adjacen subdomains into SPP, and then the SPP was sloved by Floyd algorithm, so that the minimum repeat rate requirement was met. Finally the large-scale mining traverse path planning algorithm was put forward. The simulations proved the feasibility of the presented algorithm.3) A improved ACO for mining vehicle static path planning was presented. Firstly, that traverse path is composed of two kinds of paths such as connecting path and mining path was pointed out. After expanding the world model, basic ACO was improved to meet mining real-time demand. The improved ACO was proposed and the convergence of the algorithm was proved. According to different demands of the two paths, different heuristic functions and fitness functions was set up, and then the two improved ACOs for static path planning were proposed. Through simulations, the feasibilities of the two algorithms were verified.4) A improved rolling window method for mining vehicle dynamic path planning was proposed. By using the ideology of A*algorithm, the method of choosing sub-aim points was determined. The convergence of the algorithm was proved. Then the global sub-optimality of rolling planning was proved, and that the optimal performance of the algorithm could be improved by y was also proved. The simulations show the feasibility of the algorithm. 5) Experiments were carried out to test and verify mining vehicle online path planning system, and the system was proved feasible by analysis of the experiments results.