为 6-DOF 机器人的路径规划自动选择反运动学配置

Q4 Multidisciplinary
Xuan-Vinh Nguyen, Ngoc-Lam Nguyen
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引用次数: 0

摘要

针对六自由度机器人的路径规划问题,提出了一种选择合适逆构型的自动化方法。传统上,机器人仅限于单一的固定运动配置,但现在越来越需要能够适应不同情况的机器人,特别是在未知环境中。在这项研究中,我们介绍了一种创新的方法,旨在帮助一个名为AKB-IRV1的小型工业机器人。该方法有助于机器人确定并自动选择最合适的运动构型,这对于有效的路径规划至关重要。我们通过几何分析简化了机器人关节如何工作的复杂问题,将其分解为两个阶段:计算和选择运动的最佳关节角度。我们还使用计算机模拟来评估机器人的工作空间,考虑关节角度作为约束。我们的研究结果表明,考虑关节角度会大大减少机器人的有效工作空间。我们还提出了一种机器人在规划路径时自动选择正确构型的方法,特别是在不确定的情况下。这种能力使机器人能够根据需要改变其结构,与最小化结构变化的目标保持一致。这种方法对于在陌生环境中工作的智能机器人具有很好的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
Journal of Current Science and Technology
Journal of Current Science and Technology Multidisciplinary-Multidisciplinary
CiteScore
0.80
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0.00%
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