基于多目标粒子群优化算法的斜尖柔性针穿刺路径规划
文献类型：期刊论文
| 作者 | 霍本岩; 赵新刚 ; 韩建达; 徐卫良
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| 刊名 | 机器人
 |
| 出版日期 | 2015 |
| 卷号 | 37期号:4页码:385-394 |
| 关键词 | 穿刺术 柔性针 路径规划 粒子群优化算法 |
| ISSN号 | 1002-0446 |
| 其他题名 | Puncture path planning for bevel-tip flexible needle based on multi-objective particle swarm optimization algorithm |
| 产权排序 | 1 |
| 中文摘要 | 针对斜尖柔性针在复杂环境下由入针点到达病灶位置的穿刺路径问题,提出一种基于多目标粒子群优化算法(MOPSO)的路径规划方法.对软组织内柔性针运动学模型进行分析,构建控制量与柔性针穿刺路径的关系;分析障碍物约束,建立障碍物约束的数学描述;然后,根据穿刺术的要求将穿刺精度、穿刺危险性和穿刺路径长度作为柔性针穿刺优化目标,将柔性针穿刺路径规划问题转化为多目标优化问题;建立了相应的多目标优化问题的数学模型,使用多目标粒子群优化算法对模型进行优化求解.最后通过仿真实验证明了所提方法的有效性,并仿真分析了穿刺路径的在线修正问题. 更多还原 |
| 英文摘要 | A path planning algorithm based on multi-objective particle swarm optimization (MOPSO) is proposed to plan the puncture path of bevel-tip flexible needles from the start point to the target in a complex environment. The flexible needle kinematic model in soft tissues is analyzed, and the relationship between the puncture path and controlled variables is established. Then a mathematical description of obstacles is built based on the constraint conditions of obstacles. After that, the path planning problem is transformed into a multi-objective optimization problem whose optimization objectives include puncture error, puncture danger and puncture length according to the clinical requirements of puncture. Thus, a mathematical model of the multi-objective optimization problem is set up, and MOPSO algorithm is employed to solve the multi-objective optimization problem. Finally, simulations are performed to demonstrate the effectiveness of the proposed method, and the online modification of puncture paths is analyzed. ©, 2015, Chinese Academy of Sciences. All right reserved. |
| 收录类别 | EI ; CSCD |
| 语种 | 中文 |
| CSCD记录号 | CSCD:5491369 |
| 源URL | [http://ir.sia.cn/handle/173321/16971]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 推荐引用方式 GB/T 7714 | 霍本岩,赵新刚,韩建达,等. 基于多目标粒子群优化算法的斜尖柔性针穿刺路径规划[J]. 机器人,2015,37(4):385-394. |
| APA | 霍本岩,赵新刚,韩建达,&徐卫良.(2015).基于多目标粒子群优化算法的斜尖柔性针穿刺路径规划.机器人,37(4),385-394. |
| MLA | 霍本岩,et al."基于多目标粒子群优化算法的斜尖柔性针穿刺路径规划".机器人 37.4(2015):385-394. |
入库方式： OAI收割
来源：沈阳自动化研究所
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