基于无人小车嗅觉的混合型气体溯源定位算法

A Hybrid Algorithm of Gas Traceability and Localization Based on Machine Olfactory of Unmanned Vehicles

针对大型公共区域内的危险品扩散源溯源定位问题,合理运用无人智能系统和路径规划技术,开展了三边定位法-单纯形算法的混合型算法研究。为了相对减少无人车系统在动态溯源路径中的检测节点数目,有效实现长距离快速搜索,并且保证高精确度和收敛性,首先提出一种混合型遗传算法,结合了三边定位法的迭代更新能力和单纯形算法的保守优化策略。同时在种群交叉变异中引入了组合数方法,修正了现有算法的实用性问题。仿真实验显示,该算法在收敛精度和成功率上均表现出良好的性能,定位效率相较现有算法提高了一个数量级以上。

Aiming at the problem of traceability of dangerous gas diffusion sources in large public areas,and using the unmanned intelligent vehicle system and path planning technology,a study on the hybrid algorithm of Trilateration Method(TM)and Simplex Algorithm(SA)is carried out. In order to reduce the number of detection nodes in the dynamic traceability path and effectively realize long-distance fast search,and to ensure high accuracy and convergence,this paper proposes a hybrid genetic algorithm,which combines the iterative update capability of TM and the conservative optimization ability of SA. At the same time,the combination method is introduced in the genetic structure,which improves the practicability of the existing algorithm. It is shown by simulations that the algorithm has good performance in both convergence accuracy and success rate,and the positioning efficiency is increased by more than an order of magnitude compared to existing algorithms.