Lei Yanmin, Ji Shu-jiao, Xing Xiaoxue, Ren Liye, Guan Xiu-li, Feng Zhibin
{"title":"The experimental research of dynamic path planning method based on behavior dynamics","authors":"Lei Yanmin, Ji Shu-jiao, Xing Xiaoxue, Ren Liye, Guan Xiu-li, Feng Zhibin","doi":"10.1109/MIC.2013.6758206","DOIUrl":null,"url":null,"abstract":"A kind of experiment research method was proposed in this paper to further verify dynamic path planning method in [1]. Firstly, MATLAB engine method was chosen by comparing a variety of mixed programming methods of MATLAB and Visual C++ (VC). Secondly, two experiments were studied by using two tracked robots. The first experiment was performed in static environment and the second experiment was performed in dynamic environment. The experimental results show that the dynamic path planning method in [1] is not only suitable for the dynamic environment but also suitable for the static environment. The proposed method in this paper is feasible, and it can save programming time and improve efficiency of algorithm verification.","PeriodicalId":404630,"journal":{"name":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","volume":"17 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIC.2013.6758206","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A kind of experiment research method was proposed in this paper to further verify dynamic path planning method in [1]. Firstly, MATLAB engine method was chosen by comparing a variety of mixed programming methods of MATLAB and Visual C++ (VC). Secondly, two experiments were studied by using two tracked robots. The first experiment was performed in static environment and the second experiment was performed in dynamic environment. The experimental results show that the dynamic path planning method in [1] is not only suitable for the dynamic environment but also suitable for the static environment. The proposed method in this paper is feasible, and it can save programming time and improve efficiency of algorithm verification.
为了进一步验证[1]中的动态路径规划方法,本文提出了一种实验研究方法。首先,通过比较MATLAB和Visual c++ (VC)的多种混合编程方法,选择MATLAB引擎方法。其次,利用两个履带式机器人对两个实验进行了研究。第一次实验在静态环境下进行,第二次实验在动态环境下进行。实验结果表明,[1]中的动态路径规划方法不仅适用于动态环境,也适用于静态环境。本文提出的方法是可行的,可以节省编程时间,提高算法验证效率。