{"title":"基于多目标粒子群优化的电子冰球运动控制","authors":"V. Panwar, A. Pandey, M. E. Hasan","doi":"10.30765/er.1647","DOIUrl":null,"url":null,"abstract":"This article describes the velocity-based motion and orientation control method for a differential-driven two-wheeled E-puck Robot (DDER) using the Multi-Objective Particle Swarm Optimization (MPSO) algorithm in the Virtual Robot Experimentation Platform (V-REP) software environment. The wheel velocities data and Infra-Red (IR) sensors reading make the multi-objective fitness functions for MPSO. We use front, left, and right IR sensors reading and right wheel velocity data to design the first fitness function for MPSO. Similarly, the front, left, and right IR sensors reading, and left wheel velocity data have been taken for making the second fitness function for MPSO. The multi-objective fitness functions of MPSO minimize the motion and orientation of the DDER during navigation. Due to the minimization of motion and orientation, the DDER covers less distance to reach the goal and takes less time. The Two-Dimensional (2D) and Three-Dimensional (3D) navigation results of the DDER among the scattered obstacles have been presented in the V-REP software environment. The comparative analysis with previously developed Invasive Weed Optimization (IWO) algorithm has also been performed to show the effectiveness and efficiency of the proposed MPSO algorithm.","PeriodicalId":44022,"journal":{"name":"Engineering Review","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"E-puck motion control using multi-objective particle swarm optimization\",\"authors\":\"V. Panwar, A. Pandey, M. E. Hasan\",\"doi\":\"10.30765/er.1647\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article describes the velocity-based motion and orientation control method for a differential-driven two-wheeled E-puck Robot (DDER) using the Multi-Objective Particle Swarm Optimization (MPSO) algorithm in the Virtual Robot Experimentation Platform (V-REP) software environment. The wheel velocities data and Infra-Red (IR) sensors reading make the multi-objective fitness functions for MPSO. We use front, left, and right IR sensors reading and right wheel velocity data to design the first fitness function for MPSO. Similarly, the front, left, and right IR sensors reading, and left wheel velocity data have been taken for making the second fitness function for MPSO. The multi-objective fitness functions of MPSO minimize the motion and orientation of the DDER during navigation. Due to the minimization of motion and orientation, the DDER covers less distance to reach the goal and takes less time. The Two-Dimensional (2D) and Three-Dimensional (3D) navigation results of the DDER among the scattered obstacles have been presented in the V-REP software environment. The comparative analysis with previously developed Invasive Weed Optimization (IWO) algorithm has also been performed to show the effectiveness and efficiency of the proposed MPSO algorithm.\",\"PeriodicalId\":44022,\"journal\":{\"name\":\"Engineering Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30765/er.1647\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30765/er.1647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
E-puck motion control using multi-objective particle swarm optimization
This article describes the velocity-based motion and orientation control method for a differential-driven two-wheeled E-puck Robot (DDER) using the Multi-Objective Particle Swarm Optimization (MPSO) algorithm in the Virtual Robot Experimentation Platform (V-REP) software environment. The wheel velocities data and Infra-Red (IR) sensors reading make the multi-objective fitness functions for MPSO. We use front, left, and right IR sensors reading and right wheel velocity data to design the first fitness function for MPSO. Similarly, the front, left, and right IR sensors reading, and left wheel velocity data have been taken for making the second fitness function for MPSO. The multi-objective fitness functions of MPSO minimize the motion and orientation of the DDER during navigation. Due to the minimization of motion and orientation, the DDER covers less distance to reach the goal and takes less time. The Two-Dimensional (2D) and Three-Dimensional (3D) navigation results of the DDER among the scattered obstacles have been presented in the V-REP software environment. The comparative analysis with previously developed Invasive Weed Optimization (IWO) algorithm has also been performed to show the effectiveness and efficiency of the proposed MPSO algorithm.
期刊介绍:
Engineering Review is an international journal designed to foster the exchange of ideas and transfer of knowledge between scientists and engineers involved in various engineering sciences that deal with investigations related to design, materials, technology, maintenance and manufacturing processes. It is not limited to the specific details of science and engineering but is instead devoted to a very wide range of subfields in the engineering sciences. It provides an appropriate resort for publishing the papers covering prior applications – based on the research topics comprising the entire engineering spectrum. Topics of particular interest thus include: mechanical engineering, naval architecture and marine engineering, fundamental engineering sciences, electrical engineering, computer sciences and civil engineering. Manuscripts addressing other issues may also be considered if they relate to engineering oriented subjects. The contributions, which may be analytical, numerical or experimental, should be of significance to the progress of mentioned topics. Papers that are merely illustrations of established principles or procedures generally will not be accepted. Occasionally, the magazine is ready to publish high-quality-selected papers from the conference after being renovated, expanded and written in accordance with the rules of the magazine. The high standard of excellence for any of published papers will be ensured by peer-review procedure. The journal takes into consideration only original scientific papers.