基于模型预测的AVG路径跟踪与控制研究  

The AVG Path Tracking and Control Based on Model Prediction

作　　者：莫耀华 MO Yao-hua(School of Computer Science and Network Engineering,Guangzhou University,Guangzhou Guangdong 510006,China)

机构地区：[1]广州大学计算机科学与网络工程学院,广东广州510006

出　　处：《菏泽学院学报》2023年第2期31-40,共10页Journal of Heze University

摘　　要：讨论了激光导引AGV的实时定位和绘图、轨迹规划和避障问题.对于AGV全局路径规划的设计问题,通过设计一个量化环境和优化方法,在基于传统A*算法中,将蒙特卡洛粒子滤波定位和扩展卡尔曼过滤器的融合结合起来,并消除冗余点,从而优化了算法的计算时间和路径长度.对于用传统的A*算法进行AGV路线规划的一般问题,开发了一种优化方法来平均量化的重叠点,以便优化计算时间和路线长度.最后,提出了人工势场法的改进方案,以提高复杂环境下的控制器性能.This paper discusses the real-time localization and mapping,trajectory planning and obstacle avoidance problems of laser-guided AGVs.For design of AGV global path planning,the computation time and path length of the algorithm are optimized by designing a quantization environment and an optimization method that combines Monte Carlo particle filter localization and extended Kalman filter based on traditional A*algorithm with the elimination of redundant points.For the general problem of AGV route planning with the traditional A*algorithm,an optimization method is developed to average the quantized overlap points in order to optimize the computation time and route length.Finally,an improved scheme of the artificial potential field method is proposed to improve the performance of the controller in complex environments.

关 键 词：自动导引运输车 模型预测 路径规划 避障控制 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]