{"title":"为 6-DOF 机器人的路径规划自动选择反运动学配置","authors":"Xuan-Vinh Nguyen, Ngoc-Lam Nguyen","doi":"10.59796/jcst.v14n1.2024.10","DOIUrl":null,"url":null,"abstract":"This article presents an automated technique for selecting suitable inverse configurations for the path planning of robots with six degrees of freedom (6 DOF). Traditionally, robots were limited to a single fixed configuration for movement, but now there's a growing need for robots that can adapt to different situations, especially in unknown environments. In this study, we introduce an innovative approach designed to assist a small industrial robot known as AKB-IRV1. This approach helps the robot determine and automatically select the most suitable configuration to move, which is essential for effective path planning. We simplify a complex problem related to how the robot's joints work through geometric analysis, breaking it down into two stages: calculation and selection of the best joint angles for movement. We also use computer simulations to assess the robot's workspace, considering joint angles as constraints. Our findings reveal that taking joint angles into account significantly reduces the robot's effective workspace. We also present a method for the robot to automatically choose the right configuration when planning its path, especially in uncertain situations. This ability allows the robot to change its configuration as needed, aligning with the goal of minimizing configuration changes. This method has promising applications for intelligent robots operating in unfamiliar environments.","PeriodicalId":36369,"journal":{"name":"Journal of Current Science and Technology","volume":"90 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automated Inverse Kinematics Configuration Selection for Path Planning of a 6-DOF Robot\",\"authors\":\"Xuan-Vinh Nguyen, Ngoc-Lam Nguyen\",\"doi\":\"10.59796/jcst.v14n1.2024.10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents an automated technique for selecting suitable inverse configurations for the path planning of robots with six degrees of freedom (6 DOF). Traditionally, robots were limited to a single fixed configuration for movement, but now there's a growing need for robots that can adapt to different situations, especially in unknown environments. In this study, we introduce an innovative approach designed to assist a small industrial robot known as AKB-IRV1. This approach helps the robot determine and automatically select the most suitable configuration to move, which is essential for effective path planning. We simplify a complex problem related to how the robot's joints work through geometric analysis, breaking it down into two stages: calculation and selection of the best joint angles for movement. We also use computer simulations to assess the robot's workspace, considering joint angles as constraints. Our findings reveal that taking joint angles into account significantly reduces the robot's effective workspace. We also present a method for the robot to automatically choose the right configuration when planning its path, especially in uncertain situations. This ability allows the robot to change its configuration as needed, aligning with the goal of minimizing configuration changes. This method has promising applications for intelligent robots operating in unfamiliar environments.\",\"PeriodicalId\":36369,\"journal\":{\"name\":\"Journal of Current Science and Technology\",\"volume\":\"90 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Current Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.59796/jcst.v14n1.2024.10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Multidisciplinary\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Current Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59796/jcst.v14n1.2024.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Multidisciplinary","Score":null,"Total":0}
Automated Inverse Kinematics Configuration Selection for Path Planning of a 6-DOF Robot
This article presents an automated technique for selecting suitable inverse configurations for the path planning of robots with six degrees of freedom (6 DOF). Traditionally, robots were limited to a single fixed configuration for movement, but now there's a growing need for robots that can adapt to different situations, especially in unknown environments. In this study, we introduce an innovative approach designed to assist a small industrial robot known as AKB-IRV1. This approach helps the robot determine and automatically select the most suitable configuration to move, which is essential for effective path planning. We simplify a complex problem related to how the robot's joints work through geometric analysis, breaking it down into two stages: calculation and selection of the best joint angles for movement. We also use computer simulations to assess the robot's workspace, considering joint angles as constraints. Our findings reveal that taking joint angles into account significantly reduces the robot's effective workspace. We also present a method for the robot to automatically choose the right configuration when planning its path, especially in uncertain situations. This ability allows the robot to change its configuration as needed, aligning with the goal of minimizing configuration changes. This method has promising applications for intelligent robots operating in unfamiliar environments.