CAJ | 학술논문

　　针对复杂海底环境中的潜器路径规划问题，提出了一种采用量子粒子群算法的潜器路径规划方法。该方法首先从海图中提取水深数据，基于自然邻点插值和随机中点位移插值得到密集规格水深数据。然后由此数据建立海底三维模型，确定一个路径安全性检测方案及避碰原则，将海流大小方向对潜器航行的影响和路径点的转弯角度对航行的影响转化为相应的路径长度。最后将总长度作为适应度函数，利用量子粒子群算法迭代来求取最优路径。仿真结果得到了一条安全、简洁的路径，验证了该方法的有效性和可行性。
　　침대복잡해저배경중적잠기로경규화문제，제출료일충채용양자입자군산법적잠기로경규화방법。해방법수선종해도중제취수심수거，기우자연린점삽치화수궤중점위이삽치득도밀집규격수심수거。연후유차수거건립해저삼유모형，학정일개로경안전성검측방안급피팽원칙，장해류대소방향대잠기항행적영향화로경점적전만각도대항행적영향전화위상응적로경장도。최후장총장도작위괄응도함수，이용양자입자군산법질대래구취최우로경。방진결과득도료일조안전、간길적로경，험증료해방법적유효성화가행성。
In efforts to address the submersible path planning problem in complex undersea environment , a path planning method for autonomous underwater vehicles was put forward , which is based on quantum-behaved particle swarm optimization (PSO).First, the bathymetric data was extracted from a nautical chart , and the intensive-spec-ification depth data was acquired by dealing with the natural neighbor interpolation and the random midpoint dis -placement interpolation.Next, we were able to establish the undersea 3D model and determine a path security tes-ting program, along with the principle to prevent collisions .The influence of the ocean current size , and direction on autonomous underwater vehicle navigation and the influence of the turning angle of the path points on navigation were transformed into corresponding path lengths .At last, the total length was used as the fitness function and the optimal path was obtained by iteration of quantum-behaved particle swarm optimization (QPSO).A safe and simple path was achieved as the result of the simulation , verifying effectiveness and feasibility of the method .